Abstract: A complier produces a configuration file to configure a fracturable data path of a configurable unit in a coarse-grained reconfigurable processor to concurrently generate different address sequences generated using different address associated with different operations. The fracturable data path includes multiple computation stages respectively including a pipeline register. The compiler analyzes a first address calculation and a second address calculation and assigns a first set of stages to the first operation to generate the first address sequence and a second set of stages to the second operation to generate the second address sequence using the second set of stages, based on the analysis. A configuration file for the configurable unit is generated by the compiler that assigns the first set of stages to the first operation and the second set of stages to the second operation and includes two or more immediate values for each computation stage.

Abstract: Introduced here is a computational architecture (also referred to as a “computational infrastructure”) that addresses the limitations of traditional data management solutions using a highly secure data management solution coupled with consent-based sharing. At a high level, the computational architecture applies blockchain methodologies to both transaction data and business data such that both types of data are stored “on chain” in the same computational architecture. This enables several significant advantages over traditional data management solutions with respect to data security, data ownership, data sharing, and intelligence.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: A computing method comprises generating an integrated matrix having (K+P) number of columns, columns 1 through K of the integrated matrix comprising columns 1 through K of a multiplicand matrix and columns (K+1) though P of the integrated matrix comprising addend columns. The method computes K number of products of elements of a row of the integrated matrix multiplied by elements of a column of a second multiplicand matrix; computes a (K+1) product comprising an element of an addend column multiplied by a constant; and, computes a sum of the K number of products added to the (K+1) product. The sum is equivalent to a sum of products of a column of the M×K matrix multiplied by a row of the K×N matrix added to the an element of an addend column of the integrated matrix. A computing system and a computer program product can implement the method.

Abstract: A method comprises executing (K+P) number of transposition cycles to generate a transpose-extended matrix having N rows and (K+P) columns, in which columns 1 to K comprise a transposition of a first matrix having K rows and N columns, and columns (K+1) to (K+P) comprise constants or elements of an N×1 matrix. The method includes computing a sum-product of a row of a second matrix, having M rows and N columns, multiplied by a column among columns 1 to K of the transpose-extended matrix; and, computing a second sum-product of the row of the second matrix multiplied by a column among columns (K+1) to (K+P) of the transpose-extended matrix. The sum-products can comprise gradients of input matrices. A transpose processing unit can execute the transposition cycles to read K rows of the first matrix and insert P number of constant or N×1 columns to generate the transpose-extended matrix.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: A consent block is a type of block that may be stored in a blockchain. Each consent block has an owner and may store an owner consent contract, i.e., a smart contract containing owner-specified access rules that determine who may access data assets that are stored in other blocks of the blockchain and owned by the same owner. The consent block may alternatively store a global consent contract containing global access rules that supersede owner-specified access rules. The consent block also stores a hash value determined from the consent contract and a previous hash value of the block immediately preceding the consent block. The consent contract and the position of the consent block in the blockchain are verifiable from the hash value. Each consent block, once added to the blockchain, becomes part of the immutable record of data stored in the blockchain, and therefore leaves an auditable trail.

Abstract: Disclosed are systems, hybrid compute environments, methods and computer-readable media for dynamically provisioning nodes for a workload. In the hybrid compute environment, each node communicates with a first resource manager associated with the first operating system and a second resource manager associated with a second operating system. The method includes receiving an instruction to provision at least one node in the hybrid compute environment from the first operating system to the second operating system, after provisioning the second operating system, pooling at least one signal from the resource manager associated with the at least one node, processing at least one signal from the second resource manager associated with the at least one node and consuming resources associated with the at least one node having the second operating system provisioned thereon.

Abstract: A coarse-grained reconfigurable (CGR) processor includes a configurable unit comprising a fracturable data path with a plurality of sub-paths. The fracturable data path includes multiple stages that each include an arithmetic logic unit (ALU), selection logic to select two or more inputs for the ALU, and sub-path pipeline registers. The fracturable data path also includes a first output configurable to provide first data selected from any one of the sub-path pipeline registers and a second output configurable to provide second data selected from any one of the sub-path pipeline registers. The configurable unit includes a configuration store to store configuration data to provide a two or more immediate data fields for each stage of the fracturable data path and configuration information for the ALUs, the selection logic, and to select the first data and the second data for the first output and the second output.

Abstract: A complier produces a configuration file to configure a fracturable data path of a configurable unit in a coarse-grained reconfigurable processor to concurrently generate different address sequences generated using different address associated with different operations. The fracturable data path includes multiple computation stages respectively including a pipeline register. The compiler analyzes a first address calculation and a second address calculation and assigns a first set of stages to the first operation to generate the first address sequence and a second set of stages to the second operation to generate the second address sequence using the second set of stages, based on the analysis. A configuration file for the configurable unit is generated by the compiler that assigns the first set of stages to the first operation and the second set of stages to the second operation and includes two or more immediate values for each computation stage.

Abstract: A logic unit in an array of processing units is configurable to consume source tokens and a status signal and to produce barrier tokens and an enable signal based on the source tokens and the status signal.

Abstract: A consent block is a type of block that may be stored in a blockchain. Each consent block has an owner and may store an owner consent contract, i.e., a smart contract containing owner-specified access rules that determine who may access data assets that are stored in other blocks of the blockchain and owned by the same owner. The consent block may alternatively store a global consent contract containing global access rules that supersede owner-specified access rules. The consent block also stores a hash value determined from the consent contract and a previous hash value of the block immediately preceding the consent block. The consent contract and the position of the consent block in the blockchain are verifiable from the hash value. Each consent block, once added to the blockchain, becomes part of the immutable record of data stored in the blockchain, and therefore leaves an auditable trail.

Abstract: Disclosed are systems, hybrid compute environments, methods and computer-readable media for dynamically provisioning nodes for a workload. In the hybrid compute environment, each node communicates with a first resource manager associated with the first operating system and a second resource manager associated with a second operating system. The method includes receiving an instruction to provision at least one node in the hybrid compute environment from the first operating system to the second operating system, after provisioning the second operating system, pooling at least one signal from the resource manager associated with the at least one node, processing at least one signal from the second resource manager associated with the at least one node and consuming resources associated with the at least one node having the second operating system provisioned thereon.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: A system and method of reserving resources in a compute environment are disclosed. The method embodiment comprises receiving a request for resources within a computer environment, determining at least one completion time associated with at least one resource type required by the request, and reserving resources within the computer environment based on the determine of at least the completion time. A scaled wall clock time on a per resource basis may also be used to determine what resources to reserve. The system may determine whether to perform a start time analysis or a completion time analysis or a hybrid analysis in the process of generating a co-allocation map between a first type of resource and a second type of resource in preparation for reserving resources according to the generated co-allocation map.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: Disclosed are systems, methods and computer-readable media for controlling and managing the identification and provisioning of resources within an on-demand center as well as the transfer of workload to the provisioned resources. One aspect involves creating a virtual private cluster within the on-demand center for the particular workload from a local environment. A method of managing resources between a local compute environment and an on-demand environment includes detecting an event associated with a local compute environment and based on the detected event, identifying information about the local environment, establishing communication with an on-demand compute environment and transmitting the information about the local environment to the on-demand compute environment, provisioning resources within the on-demand compute environment to substantially duplicate the local environment and transferring workload from the local-environment to the on-demand compute environment.

Abstract: Introduced here is a computational architecture (also referred to as a “computational infrastructure”) that addresses the limitations of traditional data management solutions using a highly secure data management solution coupled with consent-based sharing. At a high level, the computational architecture applies blockchain methodologies to both transaction data and business data such that both types of data are stored “on chain” in the same computational architecture. This enables several significant advantages over traditional data management solutions with respect to data security, data ownership, data sharing, and intelligence.