Optimization Specifications for CUDA Code Restructuring Tool

Handle URI:
http://hdl.handle.net/10754/623340
Title:
Optimization Specifications for CUDA Code Restructuring Tool
Authors:
Khan, Ayaz
Abstract:
In this work we have developed a restructuring software tool (RT-CUDA) following the proposed optimization specifications to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA takes a C program and convert it into an optimized CUDA kernel with user directives in a configuration file for guiding the compiler. RTCUDA also allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS enabling efficient design of linear algebra solvers. We expect RT-CUDA to be needed by many KSA industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.
Conference/Event name:
High Performance Computing Saudi Arabia (HPC Saudi) 2017
Issue Date:
13-Mar-2017
Type:
Poster
Appears in Collections:
High Performance Computing Saudi Arabia (HPC Saudi) 2017

Full metadata record

DC FieldValue Language
dc.contributor.authorKhan, Ayazen
dc.date.accessioned2017-05-04T12:33:23Z-
dc.date.available2017-05-04T12:33:23Z-
dc.date.issued2017-03-13-
dc.identifier.urihttp://hdl.handle.net/10754/623340-
dc.description.abstractIn this work we have developed a restructuring software tool (RT-CUDA) following the proposed optimization specifications to bridge the gap between high-level languages and the machine dependent CUDA environment. RT-CUDA takes a C program and convert it into an optimized CUDA kernel with user directives in a configuration file for guiding the compiler. RTCUDA also allows transparent invocation of the most optimized external math libraries like cuSparse and cuBLAS enabling efficient design of linear algebra solvers. We expect RT-CUDA to be needed by many KSA industries dealing with science and engineering simulation on massively parallel computers like NVIDIA GPUs.en
dc.titleOptimization Specifications for CUDA Code Restructuring Toolen
dc.typePosteren
dc.conference.dateMarch 13-15, 2017en
dc.conference.nameHigh Performance Computing Saudi Arabia (HPC Saudi) 2017en
dc.conference.locationKAUSTen
dc.contributor.institutionComputer Science Department, College of Computer, Qassim University, Saudi Arabiaen
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