Part 5: Performance Modeling, Prediction, and TuningInternational audienceCPU/GPU heterogeneous computing has become a tendency in scientific and engineering computing. The conventional computation models cannot be used to estimate the application running time under the CPU/GPU heterogeneous computing environment. In this paper, a new model named mHLogGP is presented on the basis of mPlogP, LogGP and LogP. In mHLogGP, he communication and memory access is abstracted based on the characteristic of CPU/GPU hybrid computing cluster. This model can be used to study the behavior of application, estimate the execution time and guide the optimization of parallel programs. The results show that the predicted running time approaches to the actual ex...
We address the problem of performance prediction for parallel programs executed on clusters of heter...
As the complexity of parallel computers grows, constraints posed by the construction of larger syste...
During recent years, the importance of utilizing more computational power in smaller computersystems...
Abstract—The use of GPU clusters for scientific applications in areas such as physics, chemistry and...
Part 6: Poster SessionsInternational audienceUsing Graphics Processing Units (GPUs) to solve general...
The availability of inexpensive “off the shelf ” machines increases the likelihood that parallel pro...
We propose a model that uses a small set of quite simple parameters to devise a proper partitioning ...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
GPU-based heterogeneous clusters continue to draw atten-tion from vendors and HPC users due to their...
We propose a massively parallel framework termed a parallel-pipeline model of execution that can be ...
The next-generation of supercomputers will feature a diverse mix of accelerator devices. The increas...
Recent advances in GPUs (graphics processing units) lead to mas-sively parallel hardware that is eas...
This thesis is composed of two parts, that relate to both parallel and heterogeneous processing. Th...
One of the major challenges faced by the HPC community today is user-friendly and accurate heterogen...
Heterogeneous parallel architectures like those comprised of CPUs and GPUs are a tantalizing compute...
We address the problem of performance prediction for parallel programs executed on clusters of heter...
As the complexity of parallel computers grows, constraints posed by the construction of larger syste...
During recent years, the importance of utilizing more computational power in smaller computersystems...
Abstract—The use of GPU clusters for scientific applications in areas such as physics, chemistry and...
Part 6: Poster SessionsInternational audienceUsing Graphics Processing Units (GPUs) to solve general...
The availability of inexpensive “off the shelf ” machines increases the likelihood that parallel pro...
We propose a model that uses a small set of quite simple parameters to devise a proper partitioning ...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
GPU-based heterogeneous clusters continue to draw atten-tion from vendors and HPC users due to their...
We propose a massively parallel framework termed a parallel-pipeline model of execution that can be ...
The next-generation of supercomputers will feature a diverse mix of accelerator devices. The increas...
Recent advances in GPUs (graphics processing units) lead to mas-sively parallel hardware that is eas...
This thesis is composed of two parts, that relate to both parallel and heterogeneous processing. Th...
One of the major challenges faced by the HPC community today is user-friendly and accurate heterogen...
Heterogeneous parallel architectures like those comprised of CPUs and GPUs are a tantalizing compute...
We address the problem of performance prediction for parallel programs executed on clusters of heter...
As the complexity of parallel computers grows, constraints posed by the construction of larger syste...
During recent years, the importance of utilizing more computational power in smaller computersystems...