Abstract: A method and a supporting node (150) for supporting a process scheduling node (110) when scheduling a process to a first execution node (130) of a cluster (120) of execution nodes (130, 140, 150) are disclosed. The supporting node (150) receives (A140), from the first execution node (130) being selected by the process scheduling node (110) for execution of the process, a request for allocation of one or more HA devices (131, 141, 151). The supporting node (150) allocates at least one HA device (141), being associated with a second execution node (140) of the cluster (120), to the first execution node (130). The supporting node (150) reduces a value representing number of HA devices (131, 141, 151) available for allocation to the first execution node (130) while taking said at least one HA device (141) into account. The supporting node (150) sends the value to the first execution node (130).

Abstract: It is disclosed a resource sharing manager, RSM, operative to provide efficient utilization of central processing units, CPUs, within virtual servers, each virtual server having an operating system, OS. The RSM dynamically obtains (902) information about ownership and sharable status of said CPUs, and dynamically determines (904) which CPUs are sharable to which virtual servers. The RSM obtains (906) information about that one or more sharable CPUs are available; and obtains (908) information about that one or more virtual servers require more processing resources. The RSM also assigns (910) a first CPU of said sharable CPUs when available, to a first virtual server of said virtual servers. Information about ownership and sharable status of the first CPU, is hence provided to the OS of the first virtual server. Overhead is reduced by circumventing a hypervisor when sharing CPUs in virtual servers. An increase in efficiency of task execution is provided.

Abstract: A memory allocation manager and a method performed thereby for managing memory allocation, within a data centre, to an application are provided. The data centre comprises at least a Central Processing Unit, CPU, pool and at least one memory pool. The method comprises receiving (210) information associated with a plurality of instances associated with an application to be initiated, wherein individual instances are associated with individual memory requirements, the information further comprising information about an internal relationship between the instances; and determining (230) for a plurality of instances, a minimum number of memory blocks and associated sizes required based on the received information, by identifying parts of memory blocks and associated sizes that may be shared by two or more instances based on their individual memory requirements and/or the internal relationship between the instances.

Abstract: A performance manager (400, 500) and a method (200) performed thereby are provided, for managing the performance of a logical server of a data center. The data center comprises at least one memory pool in which a memory block has been allocated to the logical server. The method (200) comprises determining (230) performance characteristics associated with a first portion of the memory block, comprised in a first memory unit of the at least one memory pool; and identifying (240) a second portion of the memory block, comprised in a second memory unit of the at least one memory pool, to which data of the first portion of the memory block may be migrated to apply performance characteristics associated with the second portion. The method (200) further comprises initiating migration (250) of the data to the second portion of the memory block.

Abstract: A method and a resource scheduler for enabling a computing unit to use memory resources in a remote memory pool. The resource scheduler allocates a memory unit in the remote memory pool to the computing unit for usage of memory resources in the allocated memory unit, and assigns an optical wavelength for communication between the computing unit and the allocated memory unit over an optical network. The resource scheduler further configures at least the computing unit with a first mapping between the assigned optical wavelength and the allocated memory unit. Thereby, the optical network can be utilized efficiently to achieve rapid and reliable communication of messages from the computing unit to the allocated memory unit.

Abstract: A computing unit, a memory pool and methods therein, for enabling the computing unit to use memory resources in the memory pool, e.g. as configured by a resource scheduler. When a memory unit in the memory pool is allocated to the computing unit and an optical wavelength is assigned for communication between the computing unit and the allocated memory unit over an optical network, the computing unit is configured with a first mapping between the assigned optical wavelength and the allocated memory unit. Thereby, the optical network can be utilized efficiently to achieve rapid and reliable communication of messages from the computing unit to the allocated memory unit.

Abstract: A method and a hardware acceleration managing node for managing a request for hardware acceleration (HA). The hardware acceleration managing node receives, from a HA interfacing node, the request for hardware acceleration of processing of source data. The hardware acceleration managing node sends an indication of a source memory location(s) for storing of the source data. The hardware acceleration managing node selects one or more hardware acceleration devices. The hardware acceleration managing node receives a chunk of code to be accelerated. The hardware acceleration managing node sends, to the one hardware acceleration device, a set of acceleration instructions related to the chunk of code and the indication of the source memory location. The hardware acceleration managing node receives an indication of a result memory location indicating result data. The hardware acceleration managing node sends an indication of completed hardware acceleration to the HA interfacing node.

Abstract: A method and a supporting node (150) for supporting a process scheduling node (110) when scheduling a process to a first execution node (130) of a cluster (120) of execution nodes (130, 140, 150) are disclosed. The supporting node (150) receives (A140), from the first execution node (130) being selected by the process scheduling node (110) for execution of the process, a request for allocation of one or more HA devices (131, 141, 151). The supporting node (150) allocates at least one HA device (141), being associated with a second execution node (140) of the cluster (120), to the first execution node (130). The supporting node (150) reduces a value representing number of HA devices (131, 141, 151) available for allocation to the first execution node (130) while taking said at least one HA device (141) into account. The supporting node (150) sends the value to the first execution node (130).

Abstract: A method and a hardware acceleration managing node for managing a request for hardware acceleration (HA). The hardware acceleration managing node receives, from a HA interfacing node, the request for hardware acceleration of processing of source data. The hardware acceleration managing node sends an indication of a source memory location(s) for storing of the source data. The hardware acceleration managing node selects one or more hardware acceleration devices. The hardware acceleration managing node receives a chunk of code to be accelerated. The hardware acceleration managing node sends, to the one hardware acceleration device, a set of acceleration instructions related to the chunk of code and the indication of the source memory location. The hardware acceleration managing node receives an indication of a result memory location indicating result data. The hardware acceleration managing node sends an indication of completed hardware acceleration to the HA interfacing node.

Abstract: A method and a resource scheduler for enabling a computing unit to use memory resources in a remote memory pool. The resource scheduler allocates a memory unit in the remote memory pool to the computing unit for usage of memory resources in the allocated memory unit, and assigns an optical wavelength for communication between the computing unit and the allocated memory unit over an optical network. The resource scheduler further configures at least the computing unit with a first mapping between the assigned optical wavelength and the allocated memory unit. Thereby, the optical network can be utilized efficiently to achieve rapid and reliable communication of messages from the computing unit to the allocated memory unit.

Abstract: A computing unit, a memory pool and methods therein, for enabling the computing unit to use memory resources in the memory pool, e.g. as configured by a resource scheduler. When a memory unit in the memory pool is allocated to the computing unit and an optical wavelength is assigned for communication between the computing unit and the allocated memory unit over an optical network, the computing unit is configured with a first mapping between the assigned optical wavelength and the allocated memory unit. Thereby, the optical network can be utilized efficiently to achieve rapid and reliable communication of messages from the computing unit to the allocated memory unit.

Abstract: It is disclosed a resource sharing manager, RSM, operative to provide efficient utilization of central processing units, CPUs, within virtual servers, each virtual server having an operating system, OS. The RSM dynamically obtains (902) information about ownership and sharable status of said CPUs, and dynamically determines (904) which CPUs are sharable to which virtual servers. The RSM obtains (906) information about that one or more sharable CPUs are available; and obtains (908) information about that one or more virtual servers require more processing resources. The RSM also assigns (910) a first CPU of said sharable CPUs when available, to a first virtual server of said virtual servers. Information about ownership and sharable status of the first CPU, is hence provided to the OS of the first virtual server. Overhead is reduced by circumventing a hypervisor when sharing CPUs in virtual servers. An increase in efficiency of task execution is provided.

Abstract: It is disclosed a resource sharing manager, RSM, operative to provide efficient utilization of central processing units, CPUs, within virtual servers. The RSM dynamically obtains (102) information about which CPUs are sharable to which virtual servers, (104) information about that one or more of said sharable CPUs are available, and (106) information about that one or more virtual servers of said virtual servers require more processing resources. It also dynamically assigns (108) a first CPU of said one or more sharable CPUs when available, to a first virtual server of said one or more virtual servers. This enables the first virtual server of said one or more virtual servers, to use the first CPU, until the RSM receives information that the first CPU no longer is sharable to, or needed by, the first virtual server. Overhead is reduced by circumventing a hypervisor when sharing CPUs in virtual servers.

Abstract: There is provided a method performed by a memory allocator, MA, and a MA, for allocating memory to an application on a logical server having a memory block allocated from at least one memory pool. In one action of the method, the MA 5 obtains performance characteristics associated with a first portion of the memory block and obtains performance characteristics associated with a second portion of the memory block. The MA further receives information associated with the application and selects one of the first portion and the second portion of the memory block for allocation of memory to the application, based on the received 0 information and at least one of the performance characteristics associated with the first portion of the memory block and the performance characteristics associated with the second portion of the memory block. An arrangement and methods performed therein, computer programs, computer program products and carriers are also provided.

Abstract: A memory allocation manager and a method performed thereby for managing memory allocation, within a data centre, to an application are provided. The data centre comprises at least a Central Processing Unit, CPU, pool and at least one memory pool. The method comprises receiving (210) information associated with a plurality of instances associated with an application to be initiated, wherein individual instances are associated with individual memory requirements, the information further comprising information about an internal relationship between the instances; and determining (230) for a plurality of instances, a minimum number of memory blocks and associated sizes required based on the received information, by identifying parts of memory blocks and associated sizes that may be shared by two or more instances based on their individual memory requirements and/or the internal relationship between the instances.

Abstract: A performance manager (400, 500) and a method (200) performed thereby are provided, for managing the performance of a logical server of a data center. The data center comprises at least one memory pool in which a memory block has been allocated to the logical server. The method (200) comprises determining (230) performance characteristics associated with a first portion of the memory block, comprised in a first memory unit of the at least one memory pool; and identifying (240) a second portion of the memory block, comprised in a second memory unit of the at least one memory pool, to which data of the first portion of the memory block may be migrated to apply performance characteristics associated with the second portion. The method (200) further comprises initiating migration (250) of the data to the second portion of the memory block.

Abstract: A Passive Optical Networks (PONs) structure and a remote node in such a structure constituting at least a part of a backhaul network for supporting a Radio Access Network, in which a number of radio base stations are connected to optical networks units (ONUs) of said PONs structure. The ONUs of said PONs structure are grouped between separate PONs of said PONs structure. The ONUs of a separate PON are interconnected passively through a remote node of the PON in order to separate inter base station traffic of X2 interfaces from uplink and downlink data traffic of S1 interface heading from/to a core network via an optical line terminal (OLT). The remote node comprises of power splitter for enabling interconnection between ONUs of different PONs of said PONs structure.

Abstract: A Passive Optical Networks (PONs) structure and a remote node in such a structure constituting at least a part of a backhaul network for supporting a Radio Access Network, in which a number of radio base stations are connected to optical networks units (ONUs) of said PONs structure. The ONUs of said PONs structure are grouped between separate PONs of said PONs structure. The ONUs of a separate PON are interconnected passively through a remote node of the PON in order to separate inter base station traffic of X2 interfaces from uplink and downlink data traffic of S1 interface heading from/to a core network via an optical line terminal (OLT). The remote node comprises of power splitter for enabling interconnection between ONUs of different PONs of said PONs structure.