Bodin et al., 2009 - Google Patents
Heterogeneous multicore parallel programming for graphics processing unitsBodin et al., 2009
View PDF- Document ID
- 2541925748072085137
- Author
- Bodin F
- Bihan S
- Publication year
- Publication venue
- Scientific Programming
External Links
Snippet
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 …
- XMLYCEVDHLAQEL-UHFFFAOYSA-N 2-hydroxy-2-methyl-1-phenylpropan-1-one 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 CC(C)(O)C(=O)C1=CC=CC=C1 0 abstract description 34
Classifications
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- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
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Bodin et al. | Heterogeneous multicore parallel programming for graphics processing units | |
Dubach et al. | Compiling a high-level language for GPUs: (via language support for architectures and compilers) | |
Yan et al. | JCUDA: A programmer-friendly interface for accelerating Java programs with CUDA | |
Steuwer et al. | Skelcl-a portable skeleton library for high-level gpu programming | |
Maruyama et al. | Physis: an implicitly parallel programming model for stencil computations on large-scale GPU-accelerated supercomputers | |
Dolbeau et al. | HMPP: A hybrid multi-core parallel programming environment | |
Fang et al. | Parallel programming models for heterogeneous many-cores: a comprehensive survey | |
Löff et al. | The NAS parallel benchmarks for evaluating C++ parallel programming frameworks on shared-memory architectures | |
Dominguez et al. | Caracal: Dynamic translation of runtime environments for gpus | |
Collange | Identifying scalar behavior in CUDA kernels | |
Yaneva et al. | Compiler-assisted test acceleration on gpus for embedded software | |
Rockenbach et al. | stream processing on multi-cores with GPUs: parallel programming models' challenges | |
Hayashi et al. | GPUIterator: Bridging the gap between Chapel and GPU platforms | |
Cabrera et al. | Toward performance portable programming for heterogeneous systems on a chip: A case study with qualcomm snapdragon soc | |
Moren et al. | A framework for accelerating local feature extraction with OpenCL on multi-core CPUs and co-processors | |
Szugyi et al. | Towards a multicore C++ standard template library | |
US20220365750A1 (en) | Datatype conversion technique | |
Horrigue et al. | GPU acceleration of image processing algorithm based on Matlab CUDA | |
Sakai et al. | Towards automating multi-dimensional data decomposition for executing a single-GPU code on a multi-GPU system | |
Boulos et al. | Efficient implementation of data flow graphs on multi-gpu clusters | |
Torres et al. | Supporting efficient overlapping of host-device operations for heterogeneous programming with CtrlEvents | |
Khammassi et al. | Mhpm: Multi-scale hybrid programming model: A flexible parallelization methodology | |
Fang et al. | Implementing and evaluating OpenCL on an ARMv8 multi-core CPU | |
Thorarensen | A back-end for the skepu skeleton programming library targeting the low-power multicore vision processor myriad 2 | |
Hanlon et al. | libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms |