high performance computing on graphics processing units: hgpu.org

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Performance Improvement of Multichannel Audio by Graphics Processing Units

Jose Antonio Belloch Rodriguez

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Tags: Acoustics, Algorithms, Computer science, CUDA, Databases, Filtering, nVidia, nVidia GeForce GTS 360 M, nVidia GeForce GTX 590, nVidia GeForce GTX 690, nVidia Quadro FX 5800, OpenCL, Rendering, Signal processing, Tesla C2070, Tesla K20, Thesis

October 11, 2014 by hgpu

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

Using Graphics Processing Unit to Accelerate Database Query Execution

Kamil Ksiazek, Piotr Sapiecha

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Tags: Computer science, Databases, nVidia, nVidia GeForce GTS 450, OpenCL

October 6, 2014 by hgpu

Enabling Efficient Use of MPI and PGAS Programming Models on Heterogeneous Clusters with High Performance Interconnects

Sreeram Potluri

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Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, MPI, nVidia, OpenCL, Tesla, Tesla C2075, Tesla K20, Tesla M2090

September 29, 2014 by hgpu

A Study of the Potential of Locality-Aware Thread Scheduling for GPUs

Cedric Nugteren, Gert-Jan van den Braak, Henk Corporaal

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 580, OpenCL, Task scheduling

September 28, 2014 by hgpu

Performance Evaluation of Edge Detection Techniques on GPU Using OpenCL

Aruna Dore, Sunitha Lasrado

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Tags: Computer science, Edge detection, nVidia, nVidia GeForce GTX 470, OpenCL

September 25, 2014 by hgpu

Parallel Hierarchical Clustering on the GPU

Ursula Reiterer

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Tags: Algorithms, Clustering, Computer science, nVidia, nVidia GeForce GT 650 M, OpenCL, PTX, Thesis

September 20, 2014 by hgpu

Interactive Ray Tracing with Data Locality Optimizations

Sebastian Mayr

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Tags: Algorithms, ATI, ATI Radeon HD 5650 M, Computer science, nVidia, nVidia GeForce GT 520, OpenCL, Raytracing, Rendering, Thesis

September 20, 2014 by hgpu

Parallel Primitive Optimization for GPU and Multicore

Andreas Hormandinger

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, OpenCL, Thesis

September 20, 2014 by hgpu

GPU-based NSEC3 Hash Breaking

Matthaus Wander, Lorenz Schwittmann, Christopher Boelmann, Torben Weis

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Tags: ATI, ATI Radeon HD 7970, Computer science, nVidia, nVidia GeForce GTX 690, OpenCL, Package, Security

September 19, 2014 by hgpu

Smart Multi-Task Scheduling for OpenCL Programs on CPU/GPU Heterogeneous Platforms

Yuan Wen, Zheng Wang, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 590, OpenCL, Task scheduling

September 17, 2014 by hgpu

High Performance Client-Side Web Programming with SPOC and Js_of_ocaml

Mathias Bourgoin, Emmanuel Chailloux

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Tags: Computer science, Java, nVidia, nVidia GeForce GTX 680, OpenCL

September 17, 2014 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

Performance Improvement of Multichannel Audio by Graphics Processing Units

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

Using Graphics Processing Unit to Accelerate Database Query Execution

Enabling Efficient Use of MPI and PGAS Programming Models on Heterogeneous Clusters with High Performance Interconnects

A Study of the Potential of Locality-Aware Thread Scheduling for GPUs

Performance Evaluation of Edge Detection Techniques on GPU Using OpenCL

Parallel Hierarchical Clustering on the GPU

Interactive Ray Tracing with Data Locality Optimizations

Parallel Primitive Optimization for GPU and Multicore

GPU-based NSEC3 Hash Breaking

Smart Multi-Task Scheduling for OpenCL Programs on CPU/GPU Heterogeneous Platforms

High Performance Client-Side Web Programming with SPOC and Js_of_ocaml

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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