Hybrid parallel multicore architectures based on graphics processing units (GPUs) can provide tremendous computing power. Current NVIDIA and AMD Graphics Product Group hardware display a peak performance of hundreds of gigaflops. However, exploiting GPUs from existing applications is a difficult task that requires non-portable rewriting of the code. In this paper, we present HMPP, a Heterogeneous Multicore Parallel Programming workbench with compilers, developed by CAPS entreprise, that allows the integration of heterogeneous hardware accelerators in a unintrusive manner while preserving the legacy code
High-performance computing are based more and more in heterogeneous architectures and GPGPUs have be...
In the past decade, graphics processing units (GPUs) have gained wide-spread use as general purpose ...
Multi-core processors naturally exploit thread-level parallelism (TLP). However, extracting instruct...
Heterogeneous computing system increases the performance of parallel computing in many domain of gen...
In heterogeneous environments with multi-core systems and accelerators, programming and optimizing l...
Producción CientíficaCurrent HPC clusters are composed by several machines with different computatio...
Abstract The use of GPUs for general purpose computation has increased dramatically in the past year...
International audienceHeterogeneous computing system increases the performance of parallel computing...
High-Level Heterogeneous and Hierarchical Parallel Systems (HLPGPU) aims to bring together researche...
GPUs as general purpose processors already are well adopted in scien-tific and high performance comp...
Heterogeneous computer systems are ubiquitous in all areas of computing, from mobile to high-perfor...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
The demand for high processing power together with the actual concern about power consumption has le...
Heterogeneous computing platforms support the traditional types of parallelism, such as e.g., ins...
A trend that has materialized, and has given rise to much atten-tion, is of the increasingly heterog...
High-performance computing are based more and more in heterogeneous architectures and GPGPUs have be...
In the past decade, graphics processing units (GPUs) have gained wide-spread use as general purpose ...
Multi-core processors naturally exploit thread-level parallelism (TLP). However, extracting instruct...
Heterogeneous computing system increases the performance of parallel computing in many domain of gen...
In heterogeneous environments with multi-core systems and accelerators, programming and optimizing l...
Producción CientíficaCurrent HPC clusters are composed by several machines with different computatio...
Abstract The use of GPUs for general purpose computation has increased dramatically in the past year...
International audienceHeterogeneous computing system increases the performance of parallel computing...
High-Level Heterogeneous and Hierarchical Parallel Systems (HLPGPU) aims to bring together researche...
GPUs as general purpose processors already are well adopted in scien-tific and high performance comp...
Heterogeneous computer systems are ubiquitous in all areas of computing, from mobile to high-perfor...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
The demand for high processing power together with the actual concern about power consumption has le...
Heterogeneous computing platforms support the traditional types of parallelism, such as e.g., ins...
A trend that has materialized, and has given rise to much atten-tion, is of the increasingly heterog...
High-performance computing are based more and more in heterogeneous architectures and GPGPUs have be...
In the past decade, graphics processing units (GPUs) have gained wide-spread use as general purpose ...
Multi-core processors naturally exploit thread-level parallelism (TLP). However, extracting instruct...