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Many architecture-related parameters affect application execution: number of threads, thread placement, data placement, prefetchers, core and memory frequency, SIMD, use of different levels of parallelism, precision, etc. They can help improve performance and reduce energy consumption, but poor parameter choices can also have the opposite effect. Listing and evaluating all possible combinations of these parameters quickly becomes unfeasible. For example, recent hardware developments have favored SIMD (Single Instruction Multiple Data) computing units, which can dramatically increase the number of floating point operations per second (FLOPS). However, the diversity and complexity of microarchitectures and SIMD instruction sets make them difficult to adopt in business simulation applications. The code transformations required are costly, with no guarantee of performance improvement. The same uncertainty affects other parameter choices and combinations. We present the CORHPEX (COmpiler, Runtime and Hardware Parameter EXplorer) framework, which allows parameter space explorations (PSE) to be performed on applications in order to guide parameter selection by modeling their execution times and energy consumption.

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Amphi LaBRI