Abstract: A method for configuring a large hybrid memory subsystem having a large cache size in a computing system where one or more performance metrics of the computing system are expressed as an explicit function of configuration parameters of the memory subsystem and workload parameters of the memory subsystem. The computing system hosts applications that utilize the memory subsystem, and the performance metrics cover the use of the memory subsystem by the applications. A performance goal containing values for the performance metric is identified for the computing system. These values for the performance metrics are used in the explicit function of performance metrics, configuration parameters and workload parameters to calculate values for the configuration parameters that achieve the identified performance goal. The calculated values of the configuration parameters are implemented in the memory subsystem.

Abstract: A translation table has entries that each include a share bit and a delta bit, with pointers that point to a memory block that includes reuse bits. When two translation table entries reference identical fragments in a memory block, one of the translation table entries is changed to refer to the same memory block referenced in the other translation table entry, which frees up a memory block. The share bit is set to indicate a translation table entry is sharing its memory block with another translation table entry. In addition, a translation table entry may include a private delta in the form of a pointer that references a memory fragment in the memory block that is not shared with other translation table entries. When a translation table has a private delta, its delta bit is set.

Abstract: A method for configuring a large hybrid memory subsystem having a large cache size in a computing system where one or more performance metrics of the computing system are expressed as an explicit function of configuration parameters of the memory subsystem and workload parameters of the memory subsystem. The computing system hosts applications that utilize the memory subsystem, and the performance metrics cover the use of the memory subsystem by the applications. A performance goal containing values for the performance metric is identified for the computing system. These values for the performance metrics are used in the explicit function of performance metrics, configuration parameters and workload parameters to calculate values for the configuration parameters that achieve the identified performance goal. The calculated values of the configuration parameters are implemented in the memory subsystem.

Abstract: A method for configuring a large hybrid memory subsystem having a large cache size in a computing system where one or more performance metrics of the computing system are expressed as an explicit function of configuration parameters of the memory subsystem and workload parameters of the memory subsystem. The computing system hosts applications that utilize the memory subsystem, and the performance metrics cover the use of the memory subsystem by the applications. A performance goal containing values for the performance metric is identified for the computing system. These values for the performance metrics are used in the explicit function of performance metrics, configuration parameters and workload parameters to calculate values for the configuration parameters that achieve the identified performance goal. The calculated values of the configuration parameters are implemented in the memory subsystem.

Abstract: A method for configuring a large hybrid memory subsystem having a large cache size in a computing system where one or more performance metrics of the computing system are expressed as an explicit function of configuration parameters of the memory subsystem and workload parameters of the memory subsystem. The computing system hosts applications that utilize the memory subsystem, and the performance metrics cover the use of the memory subsystem by the applications. A performance goal containing values for the performance metric is identified for the computing system. These values for the performance metrics are used in the explicit function of performance metrics, configuration parameters and workload parameters to calculate values for the configuration parameters that achieve the identified performance goal. The calculated values of the configuration parameters are implemented in the memory subsystem.

Abstract: A single instruction multiple data stream ("SIMD") processor includes multiple processing elements ("PEs"). Each PE includes a memory, a first multiplexer, an instruction register, a local instruction buffer for storing an instruction and a unit for modifying the instruction, in its entirety, to create a modified instruction. The modified instruction is stored in the local instruction buffer until it is executed. This structure modifies the instruction broadcast from the central controller of an SIMD computer in its entirety and creates modified instructions which can be unique to each PE.