high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Multi- and many-core data mining with adaptive sparse grids

Alexander Heinecke, Dirk Pfluger

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Tags: Algorithms, Computer science, Data mining, Mathematical Software, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Presentation

August 21, 2011 by hgpu

Sponge: portable stream programming on graphics engines

Amir H. Hormati, Mehrzad Samadi, Mark Woh, Trevor Mudge, Scott Mahlke

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization, Performance, Programming Languages

August 21, 2011 by hgpu

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Jing Guo, Jeyarajan Thiyagalingam, Sven-Bodo Scholz

Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Programming Languages

August 21, 2011 by hgpu

Parallel 3D multigrid methods on the STI cell BE architecture

Fabian Oboril, Jan-Philipp Weiss, Vincent Heuveline

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Tags: Cell processor, Computer science, nVidia, nVidia GeForce GTX 280, OpenCL, Performance

August 20, 2011 by hgpu

A balanced programming model for emerging heterogeneous multicore systems

Wei Liu, Brian Lewis, Xiaocheng Zhou, Hu Chen, Ying Gao, Shoumeng Yan, Sai Luo, Bratin Saha

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Tags: Computer science, Heterogeneous systems, Larrabee, OpenCL, Performance

August 19, 2011 by hgpu

A cluster for CS education in the manycore era

Joel C. Adams, Kathy Hoobeboom, Jonathan Walz

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, nVidia, OpenCL, OpenMP, OpenMPI, Performance

August 19, 2011 by hgpu

Benchmarking and modelling of POWER7, Westmere, BG/P, and GPUs: an industry case study

J. A. Herdman, W. P. Gaudin, D. Turland, S. D. Hammond

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Computer science, MPI, nVidia, nVidia GeForce GTX 285, OpenCL, Performance, Tesla C1060

August 19, 2011 by hgpu

Caracal: dynamic translation of runtime environments for GPUs

Rodrigo Dominguez, Dana Schaa, David Kaeli

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5870, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Performance, Programming Languages, PTX

August 19, 2011 by hgpu

Auto-tuning SkePU: a multi-backend skeleton programming framework for multi-GPU systems

Usman Dastgeer, Johan Enmyren, Christoph W. Kessler

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Tags: Computer science, CUDA, Data parallelism, nVidia, OpenCL, OpenMP, Package, Performance, Programming techniques, Tesla C1060

August 19, 2011 by hgpu

SkePU: a multi-backend skeleton programming library for multi-GPU systems

Johan Enmyren, Christoph W. Kessler

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Tags: Computer science, CUDA, Data parallelism, nVidia, OpenCL, OpenMP, Package, Performance, Programming techniques, Tesla C1060

August 18, 2011 by hgpu

ATI Stream Profiler: a tool to optimize an OpenCL kernel on ATI Radeon GPUs

Budirijanto Purnomo, Norman Rubin, Michael Houston

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Tags: ATI, ATI Radeon HD 5870, Computer science, OpenCL, Performance, Programming techniques

August 18, 2011 by hgpu

Maestro: Data Orchestration and Tuning for OpenCL Devices

Kyle Spafford, Jeremy Meredith, Jeffrey Vetter

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Tags: ATI, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Performance, Tesla C1060, Tesla S1070

August 18, 2011 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

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high performance computing on graphics processing units: hgpu.org

Multi- and many-core data mining with adaptive sparse grids

Sponge: portable stream programming on graphics engines

Breaking the GPU programming barrier with the auto-parallelising SAC compiler

Parallel 3D multigrid methods on the STI cell BE architecture

A balanced programming model for emerging heterogeneous multicore systems

A cluster for CS education in the manycore era

Benchmarking and modelling of POWER7, Westmere, BG/P, and GPUs: an industry case study

Caracal: dynamic translation of runtime environments for GPUs

Auto-tuning SkePU: a multi-backend skeleton programming framework for multi-GPU systems

SkePU: a multi-backend skeleton programming library for multi-GPU systems

ATI Stream Profiler: a tool to optimize an OpenCL kernel on ATI Radeon GPUs

Maestro: Data Orchestration and Tuning for OpenCL Devices

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

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

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