high performance computing on graphics processing units: hgpu.org

With the serial performance of CPUs improving exponentially through the 1980s and 1990s and then plateauing by the mid-2000s, the high-performance computing community has seen parallel computing become ubiquitous, which, in turn, has led to a proliferation of parallel programming models. This diversity in hardware platform and programming model has forced programmers to port their codes from one hardware platform to another (e.g., CUDA on Nvidia GPU to OpenCL on AMD GPU) and show reproducibility via ad-hoc testing. So, to validate reproducibility between codes, we propose Midas, a system to ensure that the results of the original code match the results of the ported code by leveraging snapshots to capture the state of a system before and after the execution of a kernel.