[HTML][HTML] A ML-based resource utilization OpenCL GPU-kernel fusion model
U Ahmed, JCW Lin, G Srivastava - Sustainable Computing: Informatics and …, 2022 - Elsevier
Massive data parallelism can be achieved by using general-purpose graphics processing
units (GPGPU) with the help of the OpenCL framework. When smaller data with higher GPU …
units (GPGPU) with the help of the OpenCL framework. When smaller data with higher GPU …
FusionCL: A machine-learning based approach for OpenCL kernel fusion to increase system performance
Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL
has resulted in greatly reducing the execution time of data-parallel applications by taking …
has resulted in greatly reducing the execution time of data-parallel applications by taking …
Efficient resource sharing through GPU virtualization on accelerated high performance computing systems
T Li, VK Narayana, T El-Ghazawi - arXiv preprint arXiv:1511.07658, 2015 - arxiv.org
The High Performance Computing (HPC) field is witnessing a widespread adoption of
Graphics Processing Units (GPUs) as co-processors for conventional homogeneous …
Graphics Processing Units (GPUs) as co-processors for conventional homogeneous …
Skmd: Single kernel on multiple devices for transparent cpu-gpu collaboration
Heterogeneous computing on CPUs and GPUs has traditionally used fixed roles for each
device: the GPU handles data parallel work by taking advantage of its massive number of …
device: the GPU handles data parallel work by taking advantage of its massive number of …
Transparent CPU-GPU collaboration for data-parallel kernels on heterogeneous systems
Heterogeneous computing on CPUs and GPUs has traditionally used fixed roles for each
device: the GPU handles data parallel work by taking advantage of its massive number of …
device: the GPU handles data parallel work by taking advantage of its massive number of …
Multitask oriented GPU resource sharing and virtualization in cloud environment
X Zhao, Y Zhang, B Su - … and Architectures for Parallel Processing: 15th …, 2015 - Springer
With the enrichment of hardware features and software development environment gradually
maturing, GPU is widely applied in the field of general-purpose computing. As a high …
maturing, GPU is widely applied in the field of general-purpose computing. As a high …
GPUPool: A holistic approach to fine-grained gpu sharing in the cloud
XS Tan, P Golikov, N Vijaykumar… - Proceedings of the …, 2022 - dl.acm.org
As Graphics Processing Units (GPUs) evolved into popular hardware accelerators for many
compute-hungry applications in the cloud, GPU virtualization has become a highly desirable …
compute-hungry applications in the cloud, GPU virtualization has become a highly desirable …
[HTML][HTML] Exploring graphics processing unit (GPU) resource sharing efficiency for high performance computing
The increasing incorporation of Graphics Processing Units (GPUs) as accelerators has been
one of the forefront High Performance Computing (HPC) trends and provides …
one of the forefront High Performance Computing (HPC) trends and provides …
AEML: An acceleration engine for multi-GPU load-balancing in distributed heterogeneous environment
Z Tang, L Du, X Zhang, L Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
For the rapid growth computation requirements in big data and artificial intelligence area,
CPU-GPU heterogeneous clusters can provide more powerful computing capacity …
CPU-GPU heterogeneous clusters can provide more powerful computing capacity …
Dynamic load balancing on multi-GPUs system for big data processing
The powerful parallel computing capability of modern GPU (Graphics Processing Unit)
processors has attracted increasing attentions of researchers and engineers who had …
processors has attracted increasing attentions of researchers and engineers who had …