Abstract—In the last three years, GPUs are more and more being used for general purpose applications instead of only for computer graphics. Programming these GPUs is a big challenge; in current GPUs the main bottleneck for many applications is not the computing power, but the memory access bandwidth. Two compile-time optimizations are presented in this paper to deal with the two most important memory access issues. To describe these optimizations, a new notation of the parallel execution of GPU programs is introduced. An implementation of the optimizations shows that performance improvements of up to 40 times are possible. I
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
GPUs are an increasingly popular implementation platform for a variety of general purpose applicatio...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
In the last three years, GPUs are more and more being used for general purpose applications instead ...
This paper presents a novel optimizing compiler for general purpose computation on graphics processi...
This paper presents a novel optimizing compiler for general purpose computation on graphics processi...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
Developing high performance GPGPU programs is challenging for application developers since the perfo...
Developing high performance GPGPU programs is challenging for application developers since the perfo...
It is well acknowledged that the dominant mechanism for scaling processor performance has become to ...
General purpose GPU (GPGPU) is an effective many-core architecture that can yield high throughput fo...
A major shift in technology from maximizing single-core performance to integrating multiple cores ha...
The continuing evolution of Graphics Processing Units (GPU) has shown rapid performance increases ov...
MATLAB is an array language that is being increasingly used for prototyping and developing code for ...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
GPUs are an increasingly popular implementation platform for a variety of general purpose applicatio...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
In the last three years, GPUs are more and more being used for general purpose applications instead ...
This paper presents a novel optimizing compiler for general purpose computation on graphics processi...
This paper presents a novel optimizing compiler for general purpose computation on graphics processi...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
Developing high performance GPGPU programs is challenging for application developers since the perfo...
Developing high performance GPGPU programs is challenging for application developers since the perfo...
It is well acknowledged that the dominant mechanism for scaling processor performance has become to ...
General purpose GPU (GPGPU) is an effective many-core architecture that can yield high throughput fo...
A major shift in technology from maximizing single-core performance to integrating multiple cores ha...
The continuing evolution of Graphics Processing Units (GPU) has shown rapid performance increases ov...
MATLAB is an array language that is being increasingly used for prototyping and developing code for ...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
GPUs are an increasingly popular implementation platform for a variety of general purpose applicatio...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...