This artifact is based on BWLOCK++, a software framework to protect the performance of GPU kernels from co-scheduled memory intensive CPU applications in platforms containing integrated GPUs. The artifact is designed to support the claims of the companion paper and contains instructions on how to build and execute BWLOCK++ on a target hardware platform
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
General purpose application development for GPUs (GPGPU) has recently gained momentum as a cost-effe...
This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-...
Integrated CPU-GPU architecture provides excellent acceleration capabilities for data parallel appli...
This artifact includes all code and scripts to reproduce the result of our paper: Automatic Horizont...
Graphics Processing Units (GPUs) have become a key technology for accelerating node performance in s...
This artifact provides the means for reproducing the experiments presented in the paper "Modeling an...
High-performance heterogeneous embedded platforms allow offloading of parallel workloads to an integ...
International audienceIn the last ten years, GPUs have dominated the market considering the computin...
As modern GPU workloads become larger and more complex, there is an ever-increasing demand for GPU c...
Heterogeneous systems combine general-purpose CPUs with domain-specific accelerators like GPUs. Rece...
Graphics Processing Units (GPUs) are evolving into powerful general purpose computing platforms. At ...
The artifact of the CAV 2021 paper entitled "Checking Data-Race Freedom of GPU Kernels, Compositiona...
Part 1: AcceleratorInternational audienceGraphics Processing Units (GPU) are widely used to accelera...
Modern computing platforms are becoming increasingly heterogeneous, combining a main processor with ...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
General purpose application development for GPUs (GPGPU) has recently gained momentum as a cost-effe...
This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-...
Integrated CPU-GPU architecture provides excellent acceleration capabilities for data parallel appli...
This artifact includes all code and scripts to reproduce the result of our paper: Automatic Horizont...
Graphics Processing Units (GPUs) have become a key technology for accelerating node performance in s...
This artifact provides the means for reproducing the experiments presented in the paper "Modeling an...
High-performance heterogeneous embedded platforms allow offloading of parallel workloads to an integ...
International audienceIn the last ten years, GPUs have dominated the market considering the computin...
As modern GPU workloads become larger and more complex, there is an ever-increasing demand for GPU c...
Heterogeneous systems combine general-purpose CPUs with domain-specific accelerators like GPUs. Rece...
Graphics Processing Units (GPUs) are evolving into powerful general purpose computing platforms. At ...
The artifact of the CAV 2021 paper entitled "Checking Data-Race Freedom of GPU Kernels, Compositiona...
Part 1: AcceleratorInternational audienceGraphics Processing Units (GPU) are widely used to accelera...
Modern computing platforms are becoming increasingly heterogeneous, combining a main processor with ...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
General purpose application development for GPUs (GPGPU) has recently gained momentum as a cost-effe...
This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-...