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LSU Doctoral Dissertations

Computer Sciences

2017

Compiler optimization

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Empirically Tuning Hpc Kernels With Ifko, Md Majedul Haque Sujon Jan 2017

Empirically Tuning Hpc Kernels With Ifko, Md Majedul Haque Sujon

LSU Doctoral Dissertations

iFKO (iterative Floating point Kernel Optimizer) is an open-source iterative empirical compilation framework which can be used to tune high performance computing (HPC) kernels. The goal of our research is to advance iterative empirical compilation to the degree that the performance it can achieve is comparable to that delivered by painstaking hand tuning in assembly. This will allow many HPC researchers to spend precious development time on higher level aspects of tuning such as parallelization, as well as enabling computational scientists to develop new algorithms that demand new high performance kernels. At present, algorithms that cannot use hand-tuned performance libraries …