Abstract: Described are self-learning systems and methods for adaptive management of memory resources within a memory hierarchy. Memory allocations associated with different active functions are organized into blocks for placement in alternative levels in a memory hierarchy optimized for different metrics of e.g. cost and performance. A host processor monitors a performance metric of the active functions, such as the number of instructions per clock cycle, and reorganizes the function-specific blocks among the levels of the hierarchy. Over time, this process tends toward block organizations that improve the performance metric.

Abstract: Described are self-learning systems and methods for adaptive management of memory resources within a memory hierarchy. Memory allocations associated with different active functions are organized into blocks for placement in alternative levels in a memory hierarchy optimized for different metrics of e.g. cost and performance. A host processor monitors a performance metric of the active functions, such as the number of instructions per clock cycle, and reorganizes the function-specific blocks among the levels of the hierarchy. Over time, this process tends toward block organizations that improve the performance metric.