Paper Info
Title
CUDACL+: a framework for GPU programs
Abstract
Graphical Processing Units (GPUs) provide an excellent execution platform for several classes of computation intensive problems. Even though there are vendor-specific Application Programming Interfaces (APIs) for GPU programming, they all share a high-level of similarity. In this extended abstract, we introduce a transformation frame-work through which sequential programs from legacy systems can be executed in any of the two common GPU programming APIs: OpenCL and CUDA. Our study shows that blocks of independent sequential code can be converted automatically to an equivalent representation in OpenCL and CUDA. In some cases, the transformation requires additional information from the programmer regarding the specific computation and the GPU configuration. Our approach provides the design decisions for a Domain-Specific Language (DSL) to specify the additional information.
Year
DOI
Venue
2011
10.1145/2048147.2048173
OOPSLA Companion
Keywords
Field
DocType
independent sequential code,gpu configuration,additional information,domain-specific language,specific computation,transformation frame-work,computation intensive problem,gpu programming,sequential program,common gpu programming apis,application program interface,domain specific language,legacy system
Programmer,Programming language,CUDA,Digital subscriber line,Computer science,Parallel computing,Application programming interface,General-purpose computing on graphics processing units,Legacy system,Computation
Conference
Citations 
PageRank 
References 
0
0.34
11
Authors
1
Name
Order
Citations
PageRank
Ferosh Jacob1829.60