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Enabling multiple accelerator acceleration for Java/OpenMP

Ronald Veldema, Thorsten Blass, Michael Philippsen

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Tags: Benchmarking, Computer science, CUDA, Java, nVidia, OpenCL, OpenMP, OpenMPI, Tesla M1060

September 9, 2011 by hgpu

A stream-computing extension to OpenMP

Antoniu Pop, Albert Cohen

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Tags: Compilers, Computer science, OpenMP, Optimization

September 9, 2011 by hgpu

Programming Many-Core Chips

Andras Vajda

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Programming techniques

September 8, 2011 by hgpu

Accelerating Clustering Coefficient Calculations on a GPU Using OPENCL

Leonid Djinevski, Igor Mishkovski, Dimitar Trajanov

Tags: Algorithms, Clustering, Computer science, Networks, OpenCL, OpenMP

September 8, 2011 by hgpu

FPGA vs. multi-core CPUs vs. GPUs: hands-on experience with a sorting application

Cristian Grozea, Zorana Bankovic, Pavel Laskov

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia Quadro FX 5600, OpenMP, Sorting

September 7, 2011 by hgpu

A breadth-first course in multicore and manycore programming

Suzanne Rivoire

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Tags: Computer science, CUDA, High-level Languages, nVidia, OpenMP, Programming techniques

August 27, 2011 by hgpu

JCudaMP: OpenMP/Java on CUDA

Georg Dotzler, Ronald Veldema, Michael Klemm

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Tags: Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 280, OpenMP, Programming Languages, Programming techniques

August 23, 2011 by hgpu

Implementing the PGI Accelerator model

Michael Wolfe

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization, Programming Languages, Tesla C1060, Tesla S1070

August 23, 2011 by hgpu

Evaluation of streaming aggregation on parallel hardware architectures

Scott Schneidert, Henrique Andrade, Bugra Gedik, Kun-Lung Wu, Dimitrios S. Nikolopoulos

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Tags: Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, OpenMP, Performance

August 22, 2011 by hgpu

Top ten ways to make formal methods for HPC practical

Ganesh Gopalakrishnan, Robert M. Kirby

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Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Performance

August 22, 2011 by hgpu

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Martin Sandrieser, Siegfried Benkner, Sabri Pllana

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, OpenMP, Presentation

August 22, 2011 by hgpu

A programming model for GPU-based parallel computing with scalability and abstraction

Balazs Domonkos, Gabor Jakab

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Tags: 3D Graphics and Realism, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenMP, Programming techniques

August 22, 2011 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Enabling multiple accelerator acceleration for Java/OpenMP

A stream-computing extension to OpenMP

Programming Many-Core Chips

Accelerating Clustering Coefficient Calculations on a GPU Using OPENCL

FPGA vs. multi-core CPUs vs. GPUs: hands-on experience with a sorting application

A breadth-first course in multicore and manycore programming

JCudaMP: OpenMP/Java on CUDA

Implementing the PGI Accelerator model

Evaluation of streaming aggregation on parallel hardware architectures

Top ten ways to make formal methods for HPC practical

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

A programming model for GPU-based parallel computing with scalability and abstraction

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Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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