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Virginia Tech

Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures

Abstract

dc:description.abstract

The use of graphics processing units (GPUs) in high-performance parallel computing continues to steadily become more prevalent, often as part of a heterogeneous system. For years, CUDA has been the de facto programming environment for nearly all general-purpose GPU (GPGPU) applications. In spite of this, the framework is available only on NVIDIA GPUs, traditionally requiring reimplementation in other frameworks in order to utilize additional multi- or many-core devices. On the other hand, OpenCL provides an open and vendor-neutral programming environment and run-time system. With implementations available for CPUs, GPUs, and other types of accelerators, OpenCL therefore holds the promise of a "write once, run anywhere" ecosystem for heterogeneous computing. Given the many similarities between CUDA and OpenCL, manually porting a CUDA application to OpenCL is almost straightforward, albeit tedious and error-prone. In response to this issue, we created CU2CL, an automated CUDA-to-OpenCL source-to-source translator that possesses a novel design and clever reuse of the Clang compiler framework. Currently, the CU2CL translator covers the primary constructs found in the CUDA Runtime API, and we have successfully translated several applications from the CUDA SDK and Rodinia benchmark suite. CU2CL's translation times are reasonable, allowing for many applications to be translated at once. The number of manual changes required after executing our translator on CUDA source is minimal, with some compiling and working with no changes at all. The performance of our automatically translated applications via CU2CL is on par with their manually ported counterparts.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science and Applications
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Martinez Arroyo, Gabriel Ernesto
Chair dc:contributor.committeechair
  • Feng, Wu-chun
Committee members dc:contributor.committeemember
  • Sandu, Adrian
  • Gardner, Mark K.

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-07282011-122302
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/34233

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Martinez Arroyo, Gabriel Ernesto. Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures. masters thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/34233