Paper Info
Title
GPUburn: A system to test and mitigate GPU hardware failures
Abstract
Due to many factors such as, high transistor density, high frequency, and low voltage, today's processors are more than ever subject to hardware failures. These errors have various impacts depending on the location of the error and the type of processor. Because of the hierarchical structure of the compute units and work scheduling, the hardware failure on GPUs affect only part of the application. In this paper we present a new methodology to characterize the hardware failures of Nvidia GPUs based on a software micro-benchmarking platform implemented in OpenCL. We also present which hardware part of TESLA architecture is more sensitive to intermittent errors, which usually appears when the processor is aging. We obtained these results by accelerating the aging process by running the processors at high temperature. We show that on GPUs, intermittent errors impact is limited to a localized architecture tile. Finally, we propose a methodology to detect, record location of defective units in order to avoid them to ensure the program correctness on such architectures, improving the GPU fault-tolerance capability and lifespan.
Year
DOI
Venue
2013
10.1109/SAMOS.2013.6621133
ICSAMOS
Keywords
Field
DocType
gpu hardware failures,program testing,defective units,software micro-benchmarking platform,fault tolerant computing,graphics processing units,hierarchical structure,tesla architecture,nvidia gpu,gpuburn,program correctness,opencl,hardware,instruction sets,aging,computer architecture,kernel
Soft error,Computer science,CUDA,Correctness,Fault tolerance,Software,General-purpose computing on graphics processing units,Low voltage,Computer hardware,Transistor,Embedded system
Conference
Citations 
PageRank 
References 
4
0.51
17
Authors
2
Name
Order
Citations
PageRank
David Defour1113.24
Eric Petit25812.73