June 2019

  1. Our work with Department of Energy/Lawrence Livermore National Lab (DOE/LLNL) on approximating scientific computation through reducing precision of floating point variables gets accepted into ICS (International Conference on Supercomputing). Acceptance rate was 45/193 = 23.3%. The work shows how you can quickly find which variables to reduce precision of and to what extent, while bounding the accuracy loss. [ PDF ] [ WWW ]
  2. A related piece of work won the best paper award at the International Supercomputing Conference (ISC) held in Frankfurt, Germany, June 16-20. The paper is titled “GPUMixer: Performance-Driven Floating-Point Tuning for GPU Scientific Applications,” and is authored by Ignacio Laguna (LLNL), Paul C. Wood (Johns Hopkins), Ranvijay Singh and Saurabh Bagchi. [ HPCWire news story ]