Skip to Main content Skip to Navigation
Reports

High Performance by Exploiting Information Locality through Reverse Computing

Mouad Bahi 1 Christine Eisenbeis 1
1 ALCHEMY - Architectures, Languages and Compilers to Harness the End of Moore Years
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In this paper we present performance results for our register rematerialization technique based on reverse recomputing. Rematerialization adds instructions and we show on one specifically designed example that reverse computing alleviates the impact of these additional instructions on performance. We also show how thread parallelism may be optimized on GPUs by performing register allocation with reverse recomputing that increases the number of threads per Streaming Multiprocessor (SM). This is done on the main kernel of Lattice Quantum ChromoDynamics (LQCD) simulation program where we gain a 10.84% speedup.
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download

https://hal.inria.fr/inria-00615493
Contributor : Mouad Bahi <>
Submitted on : Friday, August 19, 2011 - 3:53:35 PM
Last modification on : Thursday, July 8, 2021 - 3:47:43 AM
Long-term archiving on: : Monday, November 12, 2012 - 3:36:21 PM

File

bahi_information_locality.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00615493, version 1

Collections

Citation

Mouad Bahi, Christine Eisenbeis. High Performance by Exploiting Information Locality through Reverse Computing. [Research Report] 2011. ⟨inria-00615493⟩

Share

Metrics

Record views

391

Files downloads

397