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Is Source-Code Isolation Viable for Performance Characterization?

, , , and . ICPP, page 977-984. IEEE Computer Society, (2013)

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Verificarlo: Checking Floating Point Accuracy through Monte Carlo Arithmetic., , and . ARITH, page 55-62. IEEE Computer Society, (2016)Scalable Work-Stealing Load-Balancer for HPC Distributed Memory Systems., , , , , , , and . Euro-Par Workshops, volume 11339 of Lecture Notes in Computer Science, page 146-158. Springer, (2018)Comparing perturbation models for evaluating stability of neuroimaging pipelines., , , , , , and . Int. J. High Perform. Comput. Appl., (2020)ASK: Adaptive Sampling Kit for Performance Characterization., , , and . Euro-Par, volume 7484 of Lecture Notes in Computer Science, page 89-101. Springer, (2012)Is Source-Code Isolation Viable for Performance Characterization?, , , and . ICPP, page 977-984. IEEE Computer Society, (2013)Verificarlo CI: continuous integration for numerical optimization and debugging., , , , and . CoRR, (2024)Evaluating architecture and compiler design through static loop analysis., , , and . HPCS, page 535-544. IEEE, (2013)Shadow computation with BFloat16 to estimate the numerical accuracy of summations., , , and . ARITH, page 33-36. IEEE, (2021)A Study of the Effects and Benefits of Custom-Precision Mathematical Libraries for HPC Codes., , , , , , and . ARITH, page 62. IEEE, (2021)Custom-Precision Mathematical Library Explorations for Code Profiling and Optimization., , , and . ARITH, page 121-124. IEEE, (2020)