TECHNOLOGIES FOR STORAGE BLOCK VIRTUALIZATION FOR NON-VOLATILE MEMORY OVER FABRICS

Abstract

Technologies for storage block virtualization include multiple computing devices in communication over an optical fabric. A computing device receives a non-volatile memory (NVM) I/O command from an application via an optical fabric interface. The NVM I/O command is indicative of one or more virtual data storage blocks. The computing device maps the virtual data storage blocks to one or more physical data storage blocks, each of which is included in a solid-state data storage device of the computing device. The computing device performs the I/O command with the physical data storage blocks and then sends a response to the application. Mapping the virtual data storage blocks may include performing one or more data services. The computing device may be embodied as a storage sled of a data center, and the application may be executed by a compute sled of the data center. Other embodiments are described and claimed.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of U.S. Provisional Patent Application No. 62/365,969, filed Jul. 22, 2016, U.S. Provisional Patent Application No. 62/376,859, filed Aug. 18, 2016, and U.S. Provisional Patent Application No. 62/427,268, filed Nov. 29, 2016.

BACKGROUND

In a typical cloud-based computing environment (e.g., a data center), multiple compute nodes may execute workloads (e.g., processes, applications, services, etc.) on behalf of customers. During execution of workloads, the compute nodes may generate or access active or stable data that is to be stored in non-volatile storage such as solid-state drives (SSDs). The compute nodes may access remote storage using an interface to a non-volatile memory subsystem over a network fabric.

BRIEF DESCRIPTION OF THE DRAWINGS

The concepts described herein are illustrated by way of example and not by way of limitation in the accompanying figures. For simplicity and clarity of illustration, elements illustrated in the figures are not necessarily drawn to scale. Where considered appropriate, reference labels have been repeated among the figures to indicate corresponding or analogous elements.

FIG. 1 is a diagram of a conceptual overview of a data center in which one or more techniques described herein may be implemented according to various embodiments;

FIG. 2 is a diagram of an example embodiment of a logical configuration of a rack of the data center of FIG. 1;

FIG. 3 is a diagram of an example embodiment of another data center in which one or more techniques described herein may be implemented according to various embodiments;

FIG. 4 is a diagram of another example embodiment of a data center in which one or more techniques described herein may be implemented according to various embodiments;

FIG. 5 is a diagram of a connectivity scheme representative of link-layer connectivity that may be established among various sleds of the data centers of FIGS. 1, 3, and 4;

FIG. 6 is a diagram of a rack architecture that may be representative of an architecture of any particular one of the racks depicted in FIGS. 1-4 according to some embodiments;

FIG. 7 is a diagram of an example embodiment of a sled that may be used with the rack architecture of FIG. 6;

FIG. 8 is a diagram of an example embodiment of a rack architecture to provide support for sleds featuring expansion capabilities;

FIG. 9 is a diagram of an example embodiment of a rack implemented according to the rack architecture of FIG. 8;

FIG. 10 is a diagram of an example embodiment of a sled designed for use in conjunction with the rack of FIG. 9;

FIG. 11 is a diagram of an example embodiment of a data center in which one or more techniques described herein may be implemented according to various embodiments;

FIG. 12 is a simplified block diagram of at least one embodiment of a system for storage block virtualization;

FIG. 13 is a top perspective view of an example embodiment of a storage sled of FIG. 12;

FIG. 14 is a bottom perspective view of an example embodiment of a storage sled of FIG. 12;

FIG. 15 is a simplified block diagram of at least one embodiment of an environment that may be established by a storage sled of FIG. 12; and

FIG. 16 is a simplified flow diagram of at least one embodiment of a method for storage block virtualization that may be executed by a storage sled of FIGS. 12-15.

DETAILED DESCRIPTION OF THE DRAWINGS

While the concepts of the present disclosure are susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and will be described herein in detail. It should be understood, however, that there is no intent to limit the concepts of the present disclosure to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives consistent with the present disclosure and the appended claims.

References in the specification to “one embodiment,” “an embodiment,” “an illustrative embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may or may not necessarily include that particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described. Additionally, it should be appreciated that items included in a list in the form of “at least one A, B, and C” can mean (A); (B); (C); (A and B); (A and C); (B and C); or (A, B, and C). Similarly, items listed in the form of “at least one of A, B, or C” can mean (A); (B); (C); (A and B); (A and C); (B and C); or (A, B, and C).

The disclosed embodiments may be implemented, in some cases, in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on a transitory or non-transitory machine-readable (e.g., computer-readable) storage medium, which may be read and executed by one or more processors. A machine-readable storage medium may be embodied as any storage device, mechanism, or other physical structure for storing or transmitting information in a form readable by a machine (e.g., a volatile or non-volatile memory, a media disc, or other media device).

In the drawings, some structural or method features may be shown in specific arrangements and/or orderings. However, it should be appreciated that such specific arrangements and/or orderings may not be required. Rather, in some embodiments, such features may be arranged in a different manner and/or order than shown in the illustrative figures. Additionally, the inclusion of a structural or method feature in a particular figure is not meant to imply that such feature is required in all embodiments and, in some embodiments, may not be included or may be combined with other features.

FIG. 1 illustrates a conceptual overview of a data center 100 that may generally be representative of a data center or other type of computing network in/for which one or more techniques described herein may be implemented according to various embodiments. As shown in FIG. 1, data center 100 may generally contain a plurality of racks, each of which may house computing equipment comprising a respective set of physical resources. In the particular non-limiting example depicted in FIG. 1, data center 100 contains four racks 102A to 102D, which house computing equipment comprising respective sets of physical resources 105A to 105D. According to this example, a collective set of physical resources 106 of data center 100 includes the various sets of physical resources 105A to 105D that are distributed among racks 102A to 102D. Physical resources 106 may include resources of multiple types, such as—for example—processors, co-processors, accelerators, field-programmable gate arrays (FPGAs), memory, and storage. The embodiments are not limited to these examples.

The illustrative data center 100 differs from typical data centers in many ways. For example, in the illustrative embodiment, the circuit boards (“sleds”) on which components such as CPUs, memory, and other components are placed are designed for increased thermal performance In particular, in the illustrative embodiment, the sleds are shallower than typical boards. In other words, the sleds are shorter from the front to the back, where cooling fans are located. This decreases the length of the path that air must to travel across the components on the board. Further, the components on the sled are spaced further apart than in typical circuit boards, and the components are arranged to reduce or eliminate shadowing (i.e., one component in the air flow path of another component). In the illustrative embodiment, processing components such as the processors are located on a top side of a sled while near memory, such as dual inline memory modules (DIMMs), are located on a bottom side of the sled. As a result of the enhanced airflow provided by this design, the components may operate at higher frequencies and power levels than in typical systems, thereby increasing performance. Furthermore, the sleds are configured to blindly mate with power and data communication cables in each rack 102A, 102B, 102C, 102D, enhancing their ability to be quickly removed, upgraded, reinstalled, and/or replaced. Similarly, individual components located on the sleds, such as processors, accelerators, memory, and data storage drives, are configured to be easily upgraded due to their increased spacing from each other. In the illustrative embodiment, the components additionally include hardware attestation features to prove their authenticity.

Furthermore, in the illustrative embodiment, the data center 100 utilizes a single network architecture (“fabric”) that supports multiple other network architectures including Ethernet and Omni-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twisted pair cabling (e.g., Category 5, Category 5e, Category 6, etc.). Due to the high bandwidth, low latency interconnections and network architecture, the data center 100 may, in use, pool resources, such as memory, accelerators (e.g., graphics accelerators, FPGAs, application-specific integrated circuits (ASICs), etc.), and data storage drives that are physically disaggregated, and provide them to compute resources (e.g., processors) on an as needed basis, enabling the compute resources to access the pooled resources as if they were local. The illustrative data center 100 additionally receives usage information for the various resources, predicts resource usage for different types of workloads based on past resource usage, and dynamically reallocates the resources based on this information.

The racks 102A, 102B, 102C, 102D of the data center 100 may include physical design features that facilitate the automation of a variety of types of maintenance tasks. For example, data center 100 may be implemented using racks that are designed to be robotically-accessed, and to accept and house robotically-manipulatable resource sleds. Furthermore, in the illustrative embodiment, the racks 102A, 102B, 102C, 102D include integrated power sources that receive a greater voltage than is typical for power sources. The increased voltage enables the power sources to provide additional power to the components on each sled, enabling the components to operate at higher than typical frequencies.

FIG. 2 illustrates an exemplary logical configuration of a rack 202 of the data center 100. As shown in FIG. 2, rack 202 may generally house a plurality of sleds, each of which may comprise a respective set of physical resources. In the particular non-limiting example depicted in FIG. 2, rack 202 houses sleds 204-1 to 204-4 comprising respective sets of physical resources 205-1 to 205-4, each of which constitutes a portion of the collective set of physical resources 206 comprised in rack 202. With respect to FIG. 1, if rack 202 is representative of—for example—rack 102A, then physical resources 206 may correspond to the physical resources 105A comprised in rack 102A. In the context of this example, physical resources 105A may thus be made up of the respective sets of physical resources, including physical storage resources 205-1, physical accelerator resources 205-2, physical memory resources 205-3, and physical compute resources 205-5 comprised in the sleds 204-1 to 204-4 of rack 202. The embodiments are not limited to this example. Each sled may contain a pool of each of the various types of physical resources (e.g., compute, memory, accelerator, storage). By having robotically accessible and robotically manipulatable sleds comprising disaggregated resources, each type of resource can be upgraded independently of each other and at their own optimized refresh rate.

FIG. 3 illustrates an example of a data center 300 that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. In the particular non-limiting example depicted in FIG. 3, data center 300 comprises racks 302-1 to 302-32. In various embodiments, the racks of data center 300 may be arranged in such fashion as to define and/or accommodate various access pathways. For example, as shown in FIG. 3, the racks of data center 300 may be arranged in such fashion as to define and/or accommodate access pathways 311A, 311B, 311C, and 311D. In some embodiments, the presence of such access pathways may generally enable automated maintenance equipment, such as robotic maintenance equipment, to physically access the computing equipment housed in the various racks of data center 300 and perform automated maintenance tasks (e.g., replace a failed sled, upgrade a sled). In various embodiments, the dimensions of access pathways 311A, 311B, 311C, and 311D, the dimensions of racks 302-1 to 302-32, and/or one or more other aspects of the physical layout of data center 300 may be selected to facilitate such automated operations. The embodiments are not limited in this context.

FIG. 4 illustrates an example of a data center 400 that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. As shown in FIG. 4, data center 400 may feature an optical fabric 412. Optical fabric 412 may generally comprise a combination of optical signaling media (such as optical cabling) and optical switching infrastructure via which any particular sled in data center 400 can send signals to (and receive signals from) each of the other sleds in data center 400. The signaling connectivity that optical fabric 412 provides to any given sled may include connectivity both to other sleds in a same rack and sleds in other racks. In the particular non-limiting example depicted in FIG. 4, data center 400 includes four racks 402A to 402D. Racks 402A to 402D house respective pairs of sleds 404A-1 and 404A-2, 404B-1 and 404B-2, 404C-1 and 404C-2, and 404D-1 and 404D-2. Thus, in this example, data center 400 comprises a total of eight sleds. Via optical fabric 412, each such sled may possess signaling connectivity with each of the seven other sleds in data center 400. For example, via optical fabric 412, sled 404A-1 in rack 402A may possess signaling connectivity with sled 404A-2 in rack 402A, as well as the six other sleds 404B-1, 404B-2, 404C-1, 404C-2, 404D-1, and 404D-2 that are distributed among the other racks 402B, 402C, and 402D of data center 400. The embodiments are not limited to this example.

FIG. 5 illustrates an overview of a connectivity scheme 500 that may generally be representative of link-layer connectivity that may be established in some embodiments among the various sleds of a data center, such as any of example data centers 100, 300, and 400 of FIGS. 1, 3, and 4. Connectivity scheme 500 may be implemented using an optical fabric that features a dual-mode optical switching infrastructure 514. Dual-mode optical switching infrastructure 514 may generally comprise a switching infrastructure that is capable of receiving communications according to multiple link-layer protocols via a same unified set of optical signaling media, and properly switching such communications. In various embodiments, dual-mode optical switching infrastructure 514 may be implemented using one or more dual-mode optical switches 515. In various embodiments, dual-mode optical switches 515 may generally comprise high-radix switches. In some embodiments, dual-mode optical switches 515 may comprise multi-ply switches, such as four-ply switches. In various embodiments, dual-mode optical switches 515 may feature integrated silicon photonics that enable them to switch communications with significantly reduced latency in comparison to conventional switching devices. In some embodiments, dual-mode optical switches 515 may constitute leaf switches 530 in a leaf-spine architecture additionally including one or more dual-mode optical spine switches 520.

In various embodiments, dual-mode optical switches may be capable of receiving both Ethernet protocol communications carrying Internet Protocol (IP packets) and communications according to a second, high-performance computing (HPC) link-layer protocol (e.g., Intel's Omni-Path Architecture's, Infiniband) via optical signaling media of an optical fabric. As reflected in FIG. 5, with respect to any particular pair of sleds 504A and 504B possessing optical signaling connectivity to the optical fabric, connectivity scheme 500 may thus provide support for link-layer connectivity via both Ethernet links and HPC links. Thus, both Ethernet and HPC communications can be supported by a single high-bandwidth, low-latency switch fabric. The embodiments are not limited to this example.

FIG. 6 illustrates a general overview of a rack architecture 600 that may be representative of an architecture of any particular one of the racks depicted in FIGS. 1 to 4 according to some embodiments. As reflected in FIG. 6, rack architecture 600 may generally feature a plurality of sled spaces into which sleds may be inserted, each of which may be robotically-accessible via a rack access region 601. In the particular non-limiting example depicted in FIG. 6, rack architecture 600 features five sled spaces 603-1 to 603-5. Sled spaces 603-1 to 603-5 feature respective multi-purpose connector modules (MPCMs) 616-1 to 616-5.

FIG. 7 illustrates an example of a sled 704 that may be representative of a sled of such a type. As shown in FIG. 7, sled 704 may comprise a set of physical resources 705, as well as an MPCM 716 designed to couple with a counterpart MPCM when sled 704 is inserted into a sled space such as any of sled spaces 603-1 to 603-5 of FIG. 6. Sled 704 may also feature an expansion connector 717. Expansion connector 717 may generally comprise a socket, slot, or other type of connection element that is capable of accepting one or more types of expansion modules, such as an expansion sled 718. By coupling with a counterpart connector on expansion sled 718, expansion connector 717 may provide physical resources 705 with access to supplemental computing resources 705B residing on expansion sled 718. The embodiments are not limited in this context.

FIG. 8 illustrates an example of a rack architecture 800 that may be representative of a rack architecture that may be implemented in order to provide support for sleds featuring expansion capabilities, such as sled 704 of FIG. 7. In the particular non-limiting example depicted in FIG. 8, rack architecture 800 includes seven sled spaces 803-1 to 803-7, which feature respective MPCMs 816-1 to 816-7. Sled spaces 803-1 to 803-7 include respective primary regions 803-1A to 803-7A and respective expansion regions 803-1B to 803-7B. With respect to each such sled space, when the corresponding MPCM is coupled with a counterpart MPCM of an inserted sled, the primary region may generally constitute a region of the sled space that physically accommodates the inserted sled. The expansion region may generally constitute a region of the sled space that can physically accommodate an expansion module, such as expansion sled 718 of FIG. 7, in the event that the inserted sled is configured with such a module.

FIG. 9 illustrates an example of a rack 902 that may be representative of a rack implemented according to rack architecture 800 of FIG. 8 according to some embodiments. In the particular non-limiting example depicted in FIG. 9, rack 902 features seven sled spaces 903-1 to 903-7, which include respective primary regions 903-1A to 903-7A and respective expansion regions 903-1B to 903-7B. In various embodiments, temperature control in rack 902 may be implemented using an air cooling system. For example, as reflected in FIG. 9, rack 902 may feature a plurality of fans 919 that are generally arranged to provide air cooling within the various sled spaces 903-1 to 903-7. In some embodiments, the height of the sled space is greater than the conventional “1U” server height. In such embodiments, fans 919 may generally comprise relatively slow, large diameter cooling fans as compared to fans used in conventional rack configurations. Running larger diameter cooling fans at lower speeds may increase fan lifetime relative to smaller diameter cooling fans running at higher speeds while still providing the same amount of cooling. The sleds are physically shallower than conventional rack dimensions. Further, components are arranged on each sled to reduce thermal shadowing (i.e., not arranged serially in the direction of air flow). As a result, the wider, shallower sleds allow for an increase in device performance because the devices can be operated at a higher thermal envelope (e.g., 250 W) due to improved cooling (i.e., no thermal shadowing, more space between devices, more room for larger heat sinks, etc.).

MPCMs 916-1 to 916-7 may be configured to provide inserted sleds with access to power sourced by respective power modules 920-1 to 920-7, each of which may draw power from an external power source 921. In various embodiments, external power source 921 may deliver alternating current (AC) power to rack 902, and power modules 920-1 to 920-7 may be configured to convert such AC power to direct current (DC) power to be sourced to inserted sleds. In some embodiments, for example, power modules 920-1 to 920-7 may be configured to convert 277-volt AC power into 12-volt DC power for provision to inserted sleds via respective MPCMs 916-1 to 916-7. The embodiments are not limited to this example.

MPCMs 916-1 to 916-7 may also be arranged to provide inserted sleds with optical signaling connectivity to a dual-mode optical switching infrastructure 914, which may be the same as—or similar to—dual-mode optical switching infrastructure 514 of FIG. 5. In various embodiments, optical connectors contained in MPCMs 916-1 to 916-7 may be designed to couple with counterpart optical connectors contained in MPCMs of inserted sleds to provide such sleds with optical signaling connectivity to dual-mode optical switching infrastructure 914 via respective lengths of optical cabling 922-1 to 922-7. In some embodiments, each such length of optical cabling may extend from its corresponding MPCM to an optical interconnect loom 923 that is external to the sled spaces of rack 902. In various embodiments, optical interconnect loom 923 may be arranged to pass through a support post or other type of load-bearing element of rack 902. The embodiments are not limited in this context. Because inserted sleds connect to an optical switching infrastructure via MPCMs, the resources typically spent in manually configuring the rack cabling to accommodate a newly inserted sled can be saved.

FIG. 10 illustrates an example of a sled 1004 that may be representative of a sled designed for use in conjunction with rack 902 of FIG. 9 according to some embodiments. Sled 1004 may feature an MPCM 1016 that comprises an optical connector 1016A and a power connector 1016B, and that is designed to couple with a counterpart MPCM of a sled space in conjunction with insertion of MPCM 1016 into that sled space. Coupling MPCM 1016 with such a counterpart MPCM may cause power connector 1016 to couple with a power connector comprised in the counterpart MPCM. This may generally enable physical resources 1005 of sled 1004 to source power from an external source, via power connector 1016 and power transmission media 1024 that conductively couples power connector 1016 to physical resources 1005.

Sled 1004 may also include dual-mode optical network interface circuitry 1026. Dual-mode optical network interface circuitry 1026 may generally comprise circuitry that is capable of communicating over optical signaling media according to each of multiple link-layer protocols supported by dual-mode optical switching infrastructure 914 of FIG. 9. In some embodiments, dual-mode optical network interface circuitry 1026 may be capable both of Ethernet protocol communications and of communications according to a second, high-performance protocol. In various embodiments, dual-mode optical network interface circuitry 1026 may include one or more optical transceiver modules 1027, each of which may be capable of transmitting and receiving optical signals over each of one or more optical channels. The embodiments are not limited in this context.

Coupling MPCM 1016 with a counterpart MPCM of a sled space in a given rack may cause optical connector 1016A to couple with an optical connector comprised in the counterpart MPCM. This may generally establish optical connectivity between optical cabling of the sled and dual-mode optical network interface circuitry 1026, via each of a set of optical channels 1025. Dual-mode optical network interface circuitry 1026 may communicate with the physical resources 1005 of sled 1004 via electrical signaling media 1028. In addition to the dimensions of the sleds and arrangement of components on the sleds to provide improved cooling and enable operation at a relatively higher thermal envelope (e.g., 250 W), as described above with reference to FIG. 9, in some embodiments, a sled may include one or more additional features to facilitate air cooling, such as a heat pipe and/or heat sinks arranged to dissipate heat generated by physical resources 1005. It is worthy of note that although the example sled 1004 depicted in FIG. 10 does not feature an expansion connector, any given sled that features the design elements of sled 1004 may also feature an expansion connector according to some embodiments. The embodiments are not limited in this context.

FIG. 11 illustrates an example of a data center 1100 that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. As reflected in FIG. 11, a physical infrastructure management framework 1150A may be implemented to facilitate management of a physical infrastructure 1100A of data center 1100. In various embodiments, one function of physical infrastructure management framework 1150A may be to manage automated maintenance functions within data center 1100, such as the use of robotic maintenance equipment to service computing equipment within physical infrastructure 1100A. In some embodiments, physical infrastructure 1100A may feature an advanced telemetry system that performs telemetry reporting that is sufficiently robust to support remote automated management of physical infrastructure 1100A. In various embodiments, telemetry information provided by such an advanced telemetry system may support features such as failure prediction/prevention capabilities and capacity planning capabilities. In some embodiments, physical infrastructure management framework 1150A may also be configured to manage authentication of physical infrastructure components using hardware attestation techniques. For example, robots may verify the authenticity of components before installation by analyzing information collected from a radio frequency identification (RFID) tag associated with each component to be installed. The embodiments are not limited in this context.

As shown in FIG. 11, the physical infrastructure 1100A of data center 1100 may comprise an optical fabric 1112, which may include a dual-mode optical switching infrastructure 1114. Optical fabric 1112 and dual-mode optical switching infrastructure 1114 may be the same as—or similar to—optical fabric 412 of FIG. 4 and dual-mode optical switching infrastructure 514 of FIG. 5, respectively, and may provide high-bandwidth, low-latency, multi-protocol connectivity among sleds of data center 1100. As discussed above, with reference to FIG. 1, in various embodiments, the availability of such connectivity may make it feasible to disaggregate and dynamically pool resources such as accelerators, memory, and storage. In some embodiments, for example, one or more pooled accelerator sleds 1130 may be included among the physical infrastructure 1100A of data center 1100, each of which may comprise a pool of accelerator resources—such as co-processors and/or FPGAs, for example—that is globally accessible to other sleds via optical fabric 1112 and dual-mode optical switching infrastructure 1114.

In another example, in various embodiments, one or more pooled storage sleds 1132 may be included among the physical infrastructure 1100A of data center 1100, each of which may comprise a pool of storage resources that is available globally accessible to other sleds via optical fabric 1112 and dual-mode optical switching infrastructure 1114. In some embodiments, such pooled storage sleds 1132 may comprise pools of solid-state storage devices such as solid-state drives (SSDs). In various embodiments, one or more high-performance processing sleds 1134 may be included among the physical infrastructure 1100A of data center 1100. In some embodiments, high-performance processing sleds 1134 may comprise pools of high-performance processors, as well as cooling features that enhance air cooling to yield a higher thermal envelope of up to 250 W or more. In various embodiments, any given high-performance processing sled 1134 may feature an expansion connector 1117 that can accept a far memory expansion sled, such that the far memory that is locally available to that high-performance processing sled 1134 is disaggregated from the processors and near memory comprised on that sled. In some embodiments, such a high-performance processing sled 1134 may be configured with far memory using an expansion sled that comprises low-latency SSD storage. The optical infrastructure allows for compute resources on one sled to utilize remote accelerator/FPGA, memory, and/or SSD resources that are disaggregated on a sled located on the same rack or any other rack in the data center. The remote resources can be located one switch jump away or two-switch jumps away in the spine-leaf network architecture described above with reference to FIG. 5. The embodiments are not limited in this context.

In various embodiments, one or more layers of abstraction may be applied to the physical resources of physical infrastructure 1100A in order to define a virtual infrastructure, such as a software-defined infrastructure 1100B. In some embodiments, virtual computing resources 1136 of software-defined infrastructure 1100B may be allocated to support the provision of cloud services 1140. In various embodiments, particular sets of virtual computing resources 1136 may be grouped for provision to cloud services 1140 in the form of SDI services 1138. Examples of cloud services 1140 may include—without limitation—software as a service (SaaS) services 1142, platform as a service (PaaS) services 1144, and infrastructure as a service (IaaS) services 1146.

In some embodiments, management of software-defined infrastructure 1100B may be conducted using a virtual infrastructure management framework 1150B. In various embodiments, virtual infrastructure management framework 1150B may be designed to implement workload fingerprinting techniques and/or machine-learning techniques in conjunction with managing allocation of virtual computing resources 1136 and/or SDI services 1138 to cloud services 1140. In some embodiments, virtual infrastructure management framework 1150B may use/consult telemetry data in conjunction with performing such resource allocation. In various embodiments, an application/service management framework 1150C may be implemented in order to provide quality of service (QoS) management capabilities for cloud services 1140. The embodiments are not limited in this context.

Referring now to FIG. 12, in an illustrative embodiment, a system 1200 for storage block virtualization includes a storage sled 204-1 in communication with multiple other sleds 204 (e.g., one or more compute sleds 204-4 and memory sleds 204-3 as shown) over an optical fabric 1202. The system 1200 may be implemented in accordance with the data centers 100, 300, 400, 1100 described above with reference to FIGS. 1, 3, 4, and 11. In use, as described further below, the storage sled 204-1 receives non-volatile memory (NVM) over fabric input/output (I/O) commands from other entities of the system 1200, such as compute sleds 204-4. Each NVM over fabric I/O command identifies a range of virtual storage blocks for the I/O operation (e.g., for reading or writing). The storage sled 204-1 maps the range of virtual storage blocks to one or more physical storage blocks included in solid-state storage of the storage sled 204-1, and performs the I/O command with the physical storage blocks. The storage sled 204-1 may also perform one or more data services (e.g., slicing/striping, de-duplication, encryption, and/or compression) while mapping the virtual storage blocks. Thus, the system 1200 may service NVM over fabric I/O and at the same time provide data services that are transparent to applications. The data services may improve application performance and/or efficiency by improving throughput, reducing overall data storage, or otherwise improving performance. Additionally, by performing virtualization and data services using processor resources of the storage sled 204-1, the system 1200 may reduce usage of processor resources of the compute sleds 204-4, the memory sleds 204-3, and/or other compute nodes. Reducing compute node processor usage may make more compute capacity available to customers of the data center, improve power efficiency, or otherwise improve data center operations.

As shown in FIG. 12, the storage sled 204-1 illustratively includes a processor 1220, an input/output subsystem 1222, a memory 1224, a communication subsystem 1226, and multiple solid state drives (SSDs) 1228. Of course, the storage sled 204-1 may include other or additional components, such as those commonly found in rack-mounted server (e.g., various input/output devices), in other embodiments. Additionally, in some embodiments, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. For example, the memory 1224, or portions thereof, may be incorporated in the processor 1220 in some embodiments.

The processor 1220 may be embodied as any type of processor capable of performing the functions described herein. The processor 1220 may be embodied as a single or multi-core processor(s), digital signal processor, microcontroller, or other processor or processing/controlling circuit. Similarly, the memory 1224 may be embodied as any type of volatile or non-volatile memory or data storage capable of performing the functions described herein. In operation, the memory 1224 may store various data and software used during operation of the storage sled 204-1 such as operating systems, applications, programs, libraries, and drivers. The memory 1224 is communicatively coupled to the processor 1220 via the I/O subsystem 1222, which may be embodied as circuitry and/or components to facilitate input/output operations with the processor 1220, the memory 1224, and other components of the storage sled 204-1. For example, the I/O subsystem 1222 may be embodied as, or otherwise include, memory controller hubs, I/O control hubs, platform controller hubs, integrated control circuitry, firmware devices, communication links (i.e., point-to-point links, bus links, wires, cables, light guides, printed circuit board traces, etc.) and/or other components and subsystems to facilitate the input/output operations. In some embodiments, the I/O subsystem 1222 may form a portion of a system-on-a-chip (SoC) and be incorporated, along with the processor 1220, the memory 1224, and other components of the storage sled 204-1, on a single integrated circuit chip.

The communication subsystem 1226 may be configured to use any one or more communication technology (e.g., wired or wireless communications) and associated protocols (e.g., Ethernet, Bluetooth®, Wi-Fi®, WiMAX, etc.) to effect such communication. In particular, the communication subsystem 1226 may include one or more optical transceiver modules, silicon photonics devices, or other components used to communicate with other devices over the optical fabric 1202.

Each of the SSDs 1228 may be embodied as any type of solid-state, non-volatile storage device or devices configured for short-term or long-term storage of data such as, for example, memory devices and circuits, memory cards, solid-state drives, or other data storage devices. As shown, the illustrative storage sled 204-1 includes eight SSDs 1228-1 to 1228-8. In other embodiments, each storage sled 204-1 may include a different number of SSDs 1228, and in some embodiments the SSDs 1228 may be hot-pluggable, replaceable, or otherwise configurable.

As shown, each storage sled 204-1 may also include one or more peripheral devices 1230. The peripheral devices 1230 may include any number of additional I/O devices, interface devices, sensors, and/or other peripheral devices. For example, in some embodiments, the peripheral devices 1230 may include a display, touch screen, graphics circuitry, keyboard, mouse, speaker system, microphone, network interface, and/or other input/output devices, interface devices, and/or peripheral devices.

Referring now to FIG. 13, a top perspective view of an illustrative storage sled 204-1 is shown. As illustrated, the storage sled 204-1 includes a top side 1302. The storage sled 204-1 includes two processors 1220 and a communications subsystem 1226 positioned on the top side 1302. The storage sled 204-1 further includes a storage cage 1304 positioned at one end of the storage sled 204-1 that includes the physical storage resources 205-1. The illustrative storage sled 204-1 includes sixteen SSDs 1228 mounted to slots in the storage cage 1304. As shown, the storage cage 1304 extends above and below the top side 1302 of the storage sled 204-1.

Referring now to FIG. 14, a bottom perspective view of the illustrative storage sled 204-1 is shown. As illustrated, the storage sled 204-1 also includes a bottom side 1402. The storage sled 204-1 includes memory 1224 positioned within slots on the bottom side 1402. In some examples, the memory 1224 may include multiple DIMMs. For these examples, each DIMM may include volatile and/or non-volatile types of memory. Volatile types of memory may include, but are not limited to, RAM, DRAM, double data rate synchronous dynamic RAM (DDR SDRAM), static random-access memory (SRAM), thyristor RAM (T-RAM) or zero-capacitor RAM (Z-RAM). Non-volatile types of memory may include, but are not limited to, non-volatile types of memory that may be byte or block addressable. Block addressable or byte addressable non-volatile types of memory may include, but are not limited to, 3-dimensional (3-D) cross-point memory, memory that uses chalcogenide phase change material (e.g., chalcogenide glass), multi-threshold level NAND flash memory, NOR flash memory, single or multi-level phase change memory (PCM), resistive memory, nanowire memory, ferroelectric transistor random access memory (FeTRAM), magnetoresistive random access memory (MRAM) memory that incorporates memristor technology, or spin transfer torque MRAM (STT-MRAM), or a combination of any of the above, or other non-volatile types of memory. FIG. 14 also illustrates the storage cage 1304 positioned at the end of the storage sled 204-1 that includes the SSDs 1228. As shown, the storage cage 1304 extends above and below the bottom side 1402 of the storage sled 204-1

Referring now to FIG. 15, in an illustrative embodiment, the storage sled 204-1 establishes an environment 1500 during operation. The illustrative environment 1500 includes a non-volatile memory (NVM) over fabric layer 1502, a block virtualization layer 1504, and a physical block layer 1516. The various components of the environment 1500 may be embodied as hardware, firmware, software, or a combination thereof. As such, in some embodiments, one or more of the components of the environment 1500 may be embodied as circuitry or collection of electrical devices (e.g., NVM over fabric circuitry 1502, block virtualization circuitry 1504, and/or physical block circuitry 1516). It should be appreciated that, in such embodiments, one or more of the NVM over fabric circuitry 1502, the block virtualization circuitry 1504, and/or the physical block circuitry 1516 may form a portion of the processor 1220, the I/O subsystem 1222, the SSDs 1228, and/or other components of the storage sled 204-1. Additionally, in some embodiments, one or more of the illustrative components may form a portion of another component and/or one or more of the illustrative components may be independent of one another.

The NVM over fabric layer 1502 is configured to receive an NVM I/O command from an application via an optical fabric 1202 interface. The NVM I/O command is indicative of one or more virtual data storage blocks. The NVM I/O command may be embodied as, for example, a read command or a write command. The NVM over fabric layer 1502 is further configured to send a response associated with the NVM I/O command to the application via the optical fabric 1202 interface in response performing the NVM I/O command as described further below.

The block virtualization layer 1504 is configured to map the one or more virtual data storage blocks to one or more physical data storage blocks. Each of the physical data storage blocks is included in an SSD 1228 of the storage sled 204-1. In some embodiments, the block virtualization layer 1504 further includes a data services layer 1506 configured to perform one or more data services on the application data included in the virtual data storage blocks and/or the physical data storage blocks. In some embodiments, the data services layer 1506 may be configured to process the one or more physical data storage blocks and/or application data included in the one or more virtual data storage blocks, for example by slicing or striping the physical data storage blocks across multiple SSDs 1228, by de-duplicating the physical data storage blocks, by encrypting the application data, and/or by compressing the application data. In some embodiments, those functions may be performed by one or more sub-components, such as a slicing/striping service 1508, an encryption service 1510, a de-duplication service 1512, and/or a data compression service 1514.

The physical block layer 1516 is configured to perform the non-volatile memory I/O command with the one or more physical data storage blocks. For example, the physical block layer 1516 may be configured to read a data value from the one or more physical data storage blocks or to write a data value specified by the NVM I/O command to the one or more physical data storage blocks.

Referring now to FIG. 16, in use, the storage sled 204-1 may execute a method 1600 for storage block virtualization. It should be appreciated that, in some embodiments, the method 1600 may be embodied as various instructions stored on a computer-readable media, which may be executed by the processor 1220, the I/O subsystem 1222, and/or other components of the storage sled 204-1 to cause the storage sled 204-1 to perform the method 1600. The computer-readable media may be embodied as any type of media capable of being read by the storage sled 204-1 including, but not limited to, the memory 1224, an SSD 1228, firmware devices, and/or other media. Additionally or alternatively, it should be appreciated that, in some embodiments, the operations of the method 1600 may be performed by one or more components of the environment 1500 of the storage sled 204-1 as shown in FIG. 15.

The method 1600 begins in block 1602, in which the storage sled 204-1 receives a NVM over fabric I/O command from an application via the optical fabric 1202. The application may be embodied as any application, thread, virtual machine, or other workload executed by the system 1200. In particular, the application may be embodied as a workload executed by a compute sled 204-4, an accelerator sled 204-2, and/or other sled 204 of the system 1200. In some embodiments, the application may include cloud-based client applications (e.g., web applications, database applications, etc.), middleware, libraries, and/or system services (e.g., active data services, ephemeral data services, filesystems, or other storage interfaces). The NVM over fabric I/O command specifies an I/O command (e.g., read, write, etc.) to be performed on an associated range of virtual storage blocks. Each virtual storage block may be embodied as any fixed-sized storage unit used by the application. For example, each virtual storage block may be embodied as a logical block that is identified by a logical block address (LBA). The NVM over fabric I/O command may also include data associated with the I/O command (e.g., data to be written). In some embodiments, the I/O command may reference the data associated with the I/O command, for example by including one or more pointers, scatter-gather lists, or other identifying data. The NVM over fabric I/O command may be embodied as, for example, an NVM Express (NVMe) over Fabric capsule.

In block 1604, the storage sled 204-1 maps the virtual storage block(s) to one or more physical storage block(s). Each of the physical storage blocks may be embodied as any fixed-sized storage unit of an SSD 1228 of the storage sled 204-1. In particular, each physical storage block may be a logical block that is identified by a logical block address (LBA) of an SSD 1228. The storage sled 204-1 may use any appropriate algorithm to allocate or otherwise manage the physical storage blocks. For example, in some embodiments, the virtual storage blocks may be mapped one-to-one to physical storage blocks. Additionally or alternatively, in some embodiments the virtual storage blocks may be mapped to a different number of physical storage blocks. For example, as described further below, in some embodiments the virtual storage blocks may be mapped to a smaller number of physical storage blocks, which may reduce the total amount of storage space required for the application data in the SSDs 1228.

In block 1606, the storage sled 204-1 may perform one or more data services on the physical storage block(s). The data services may include any processing, post-processing, or other operations performed on the physical storage blocks or the data included in the physical storage blocks. In some embodiments, in block 1608 the storage sled 204-1 may slice or stripe the physical storage blocks over multiple SSDs 1228. For example, the storage sled 204-1 may distribute the physical storage blocks for sequential virtual storage blocks onto different physical SSDs 1228 and/or mirror physical storage blocks among multiple physical SSDs 1228. Slicing or striping the physical storage blocks may improve performance by allowing multiple SSDs 1228 to be used for servicing each NVM over fabric I/O command, which in turn may allow the storage sled 204-1 to fully utilize bandwidth available over the optical fabric 1202. As another example, slicing or striping the physical storage blocks may provide data redundancy and improve fault-tolerance. In some embodiments, in block 1610 the storage sled 204-1 may de-duplicate multiple physical storage blocks. For example, the storage sled 204-1 may identify virtual storage blocks (which may originate from different applications) that contain identical data and map those virtual storage blocks to the same physical storage block. De-duplicating physical storage blocks may reduce the total amount of storage space required in the SSDs 1228.

In block 1612, the storage sled 204-1 may perform one or more data services on the application data included in the virtual storage blocks. The data services may be performed on the application data as a whole, or in some embodiments may be performed on a block-by-block basis. In some embodiments, in block 1614 the storage sled 204-1 may encrypt the application data. The storage sled 204-1 may encrypt the data included in an entire range of virtual storage blocks, or in some embodiments may encrypt each block separately. Additionally, although described as encrypting the virtual storage blocks, it should be understood that in some embodiments the storage sled 204-1 may encrypt the physical storage blocks (for example, after compression or de-duplication). In some embodiments, in block 1616 the storage sled 204-1 may compress the application data. Compressing the application data from the virtual data blocks used by the application may allow the compressed data to be stored in a smaller number of physical data blocks.

In block 1618, the storage sled 204-1 performs the NVM I/O command on the physical storage blocks. In particular, the storage sled 204-1 may issue one or more I/O commands to the SSDs 1228 to perform the NVM I/O command In some embodiments, in block 1620 the storage sled 204-1 may write data to the physical storage blocks of the SSDs 1228. In some embodiments, the storage sled 204-1 may perform one or more direct memory access operations, remote direct memory access operations, fabric data transfers, or other operations to read the data of the virtual storage blocks from the application (e.g., from the memory of a compute sled 204-4 and/or memory sled 204-3). In some embodiments, in block 1622 the storage sled 204-1 may read data from the physical storage blocks of the SSDs 1228.

In block 1624, the storage sled 204-1 sends a response to the NVM I/O command to the application. The response may be embodied as, for example, an NVMe over Fabrics response capsule. The response may indicate the status of the NVM I/O command, including whether the NVM I/O command completed successfully. For NVM over fabric read requests, the response may also include or reference the data of the virtual storage blocks. For example, the storage sled 204-1 may perform one or more direct memory access operations, remote direct memory access operations, fabric data transfers, or other operations to send the data of the virtual storage blocks to the application. After sending the response, the method 1600 loops back to block 1602 to continue processing NVM over fabric I/O commands.

EXAMPLES

Illustrative examples of the technologies disclosed herein are provided below. An embodiment of the technologies may include any one or more, and any combination of, the examples described below.

Example 1 includes a computing device for virtualized block data access, the computing device comprising: a non-volatile memory over fabric layer to receive a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks; a block virtualization layer to map the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device; and a physical block layer to perform the non-volatile memory I/O command with the one or more physical data storage blocks; wherein the non-volatile memory over fabric layer is further to send a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performance of the non-volatile memory I/O command.

Example 2 includes the subject matter of Example 1, and wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process the one or more physical data storage blocks.

Example 3 includes the subject matter of any of Examples 1 and 2, and wherein to process the one or more physical data storage blocks comprises to slice or to stripe the one or more physical data storage blocks across a plurality of solid-state data storage devices of the computing device.

Example 4 includes the subject matter of any of Examples 1-3, and wherein to process the one or more physical data storage blocks comprises to de-duplicate the one or more physical data storage blocks.

Example 5 includes the subject matter of any of Examples 1-4, and wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process application data included in the one or more virtual data storage blocks.

Example 6 includes the subject matter of any of Examples 1-5, and wherein to process the application data included in the one or more virtual data storage blocks comprises to encrypt the application data.

Example 7 includes the subject matter of any of Examples 1-6, and wherein to process the application data included in the one or more virtual data storage blocks comprises to compress the application data.

Example 8 includes the subject matter of any of Examples 1-7, and wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to perform a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

Example 9 includes the subject matter of any of Examples 1-8, and wherein: the non-volatile memory I/O command comprises a read command; to perform the non-volatile memory I/O command comprises to read a data value from the one or more physical data storage blocks; and to send the response to the application comprises to send the data value to the application via the optical fabric interface.

Example 10 includes the subject matter of any of Examples 1-9, and wherein: the non-volatile memory I/O command comprises a write command, wherein the write command is indicative of a data value; and to perform the non-volatile memory I/O command comprises to write the data value to the one or more physical data storage blocks.

Example 11 includes the subject matter of any of Examples 1-10, and wherein: the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and the application comprises a workload executed by a compute sled of the data center.

Example 12 includes a method for virtualized block data access, the method comprising: receiving, by a computing device, a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks; mapping, by the computing device, the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device; performing, by the computing device, the non-volatile memory I/O command with the one or more physical data storage blocks; and sending, by the computing device, a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performing the non-volatile memory I/O command.

Example 13 includes the subject matter of Example 12, and wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises processing the one or more physical data storage blocks.

Example 14 includes the subject matter of any of Examples 12 and 13, and wherein processing the one or more physical data storage blocks comprises slicing or striping the one or more physical data storage blocks across a plurality of solid-state data storage devices of the computing device.

Example 15 includes the subject matter of any of Examples 12-14, and wherein processing the one or more physical data storage blocks comprises de-duplicating the one or more physical data storage blocks.

Example 16 includes the subject matter of any of Examples 12-15, and wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises processing application data included in the one or more virtual data storage blocks.

Example 17 includes the subject matter of any of Examples 12-16, and wherein processing the application data included in the one or more virtual data storage blocks comprises encrypting the application data.

Example 18 includes the subject matter of any of Examples 12-17, and wherein processing the application data included in the one or more virtual data storage blocks comprises compressing the application data.

Example 19 includes the subject matter of any of Examples 12-18, and wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises performing a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

Example 20 includes the subject matter of any of Examples 12-19, and wherein: receiving the non-volatile memory I/O command comprises receiving a read command; performing the non-volatile memory I/O command comprises reading a data value from the one or more physical data storage blocks; and sending the response to the application comprises sending the data value to the application via the optical fabric interface.

Example 21 includes the subject matter of any of Examples 12-20, and wherein: receiving the non-volatile memory I/O command comprises receiving a write command, wherein the write command is indicative of a data value; and performing the non-volatile memory I/O command comprises writing the data value to the one or more physical data storage blocks.

Example 22 includes the subject matter of any of Examples 12-21, and wherein: the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and the application comprises a workload executed by a compute sled of the data center.

Example 23 includes a computing device comprising: a processor; and a memory having stored therein a plurality of instructions that when executed by the processor cause the computing device to perform the method of any of Examples 12-22.

Example 24 includes one or more machine readable storage media comprising a plurality of instructions stored thereon that in response to being executed result in a computing device performing the method of any of Examples 12-22.

Example 25 includes a computing device comprising means for performing the method of any of Examples 12-22.

Example 26 includes a computing device for virtualized block data access, the computing device comprising: means for receiving a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks; means for mapping the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device; means for performing the non-volatile memory I/O command with the one or more physical data storage blocks; and means for sending a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performing the non-volatile memory I/O command.

Example 27 includes the subject matter of Example 26, and wherein the means for mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises means for processing the one or more physical data storage blocks.

Example 28 includes the subject matter of any of Examples 26 and 27, and wherein the means for processing the one or more physical data storage blocks comprises means for slicing or striping the one or more physical data storage blocks across a plurality of solid-state data storage devices of the computing device.

Example 29 includes the subject matter of any of Examples 26-28, and wherein the means for processing the one or more physical data storage blocks comprises means for de-duplicating the one or more physical data storage blocks.

Example 30 includes the subject matter of any of Examples 26-29, and wherein the means for mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises means for processing application data included in the one or more virtual data storage blocks.

Example 31 includes the subject matter of any of Examples 26-30, and wherein the means for processing the application data included in the one or more virtual data storage blocks comprises means for encrypting the application data.

Example 32 includes the subject matter of any of Examples 26-31, and wherein the means for processing the application data included in the one or more virtual data storage blocks comprises means for compressing the application data.

Example 33 includes the subject matter of any of Examples 26-32, and wherein the means for mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises means for performing a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

Example 34 includes the subject matter of any of Examples 26-33, and wherein: the means for receiving the non-volatile memory I/O command comprises means for receiving a read command; the means for performing the non-volatile memory I/O command comprises means for reading a data value from the one or more physical data storage blocks; and the means for sending the response to the application comprises means for sending the data value to the application via the optical fabric interface.

Example 35 includes the subject matter of any of Examples 26-34, and wherein: the means for receiving the non-volatile memory I/O command comprises means for receiving a write command, wherein the write command is indicative of a data value; and the means for performing the non-volatile memory I/O command comprises means for writing the data value to the one or more physical data storage blocks.

Example 36 includes the subject matter of any of Examples 26-35, and wherein: the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and the application comprises a workload executed by a compute sled of the data center.

Claims

1. A computing device for virtualized block data access, the computing device comprising:

a non-volatile memory over fabric layer to receive a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks;

a block virtualization layer to map the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device; and

a physical block layer to perform the non-volatile memory I/O command with the one or more physical data storage blocks;

wherein the non-volatile memory over fabric layer is further to send a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performance of the non-volatile memory I/O command.

2. The computing device of claim 1, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process the one or more physical data storage blocks.

3. The computing device of claim 2, wherein to process the one or more physical data storage blocks comprises to slice or to stripe the one or more physical data storage blocks across a plurality of solid-state data storage devices of the computing device.

4. The computing device of claim 2, wherein to process the one or more physical data storage blocks comprises to de-duplicate the one or more physical data storage blocks.

5. The computing device of claim 1, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process application data included in the one or more virtual data storage blocks.

6. The computing device of claim 5, wherein to process the application data included in the one or more virtual data storage blocks comprises to encrypt the application data.

7. The computing device of claim 5, wherein to process the application data included in the one or more virtual data storage blocks comprises to compress the application data.

8. The computing device of claim 1, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to perform a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

9. The computing device of claim 1, wherein:

the non-volatile memory I/O command comprises a read command;

to perform the non-volatile memory I/O command comprises to read a data value from the one or more physical data storage blocks; and

to send the response to the application comprises to send the data value to the application via the optical fabric interface.

10. The computing device of claim 1, wherein:

the non-volatile memory I/O command comprises a write command, wherein the write command is indicative of a data value; and

to perform the non-volatile memory I/O command comprises to write the data value to the one or more physical data storage blocks.

11. The computing device of claim 1, wherein:

the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and

the application comprises a workload executed by a compute sled of the data center.

12. A method for virtualized block data access, the method comprising:

receiving, by a computing device, a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks;

mapping, by the computing device, the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device;

performing, by the computing device, the non-volatile memory I/O command with the one or more physical data storage blocks; and

sending, by the computing device, a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performing the non-volatile memory I/O command.

13. The method of claim 12, wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises processing the one or more physical data storage blocks.

14. The method of claim 12, wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises processing application data included in the one or more virtual data storage blocks.

15. The method of claim 12, wherein mapping the one or more virtual data storage blocks to the one or more physical data storage blocks comprises performing a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

16. The method of claim 12, wherein:

receiving the non-volatile memory I/O command comprises receiving a read command;

performing the non-volatile memory I/O command comprises reading a data value from the one or more physical data storage blocks; and

sending the response to the application comprises sending the data value to the application via the optical fabric interface.

17. The method of claim 12, wherein:

receiving the non-volatile memory I/O command comprises receiving a write command, wherein the write command is indicative of a data value; and

performing the non-volatile memory I/O command comprises writing the data value to the one or more physical data storage blocks.

18. The method of claim 12, wherein:

the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and

the application comprises a workload executed by a compute sled of the data center.

19. One or more computer-readable storage media comprising a plurality of instructions that in response to being executed cause a computing device to:

receive a non-volatile memory input/output (I/O) command from an application via an optical fabric interface, wherein the non-volatile memory I/O command is indicative of one or more virtual data storage blocks;

map the one or more virtual data storage blocks to one or more physical data storage blocks, wherein each of the physical data storage blocks is included in a solid-state data storage device of the computing device;

perform the non-volatile memory I/O command with the one or more physical data storage blocks; and

send a response associated with the non-volatile memory I/O command to the application via the optical fabric interface in response to performing the non-volatile memory I/O command.

20. The one or more computer-readable storage media of claim 19, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process the one or more physical data storage blocks.

21. The one or more computer-readable storage media of claim 19, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to process application data included in the one or more virtual data storage blocks.

22. The one or more computer-readable storage media of claim 19, wherein to map the one or more virtual data storage blocks to the one or more physical data storage blocks comprises to perform a data service on the application data included in the one or more virtual data storage blocks or the one or more physical data storage blocks.

23. The one or more computer-readable storage media of claim 19, wherein:

to receive the non-volatile memory I/O command comprises to receive a read command;

to perform the non-volatile memory I/O command comprises to read a data value from the one or more physical data storage blocks; and

to send the response to the application comprises to send the data value to the application via the optical fabric interface.

24. The one or more computer-readable storage media of claim 19, wherein:

to receive the non-volatile memory I/O command comprises to receive a write command, wherein the write command is indicative of a data value; and

to perform the non-volatile memory I/O command comprises to write the data value to the one or more physical data storage blocks.

25. The one or more computer-readable storage media of claim 19, wherein:

the computing device comprises a storage sled of a data center, wherein the storage sled comprises a processor and a plurality of solid-state storage devices; and

the application comprises a workload executed by a compute sled of the data center.