Machine learning for workloads for instruction set architecture optimization
Abstract:
An apparatus for machine learning for workloads for ISA optimization is disclosed. The apparatus includes a processor and a memory that stores code executable by the processor. The executable code is executable to run program code to service a workload with a default instruction set of the processor, identify an instruction sequence from execution results for the workload, the instruction sequence called repeatedly during execution for the workload, and generate a custom instruction that includes the instruction sequence. The executable code is executable to write the custom instruction to a writable area of processor memory storing the default instruction set, recompile program code used to service the workload, where the recompiled program code includes the custom instruction, and run the recompiled program code to service the workload.
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