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CAVE-CL: An OpenCL version of the package for detection and quantitative analysis of internal cavities in a system of overlapping balls: application to proteins

Jan Busa Jr., Jan Busa, Shura Hayryan, Chin-Kun Hu, Ming-Chya Wu

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Tags: Algorithms, Biology, Computer physics, Fortran, nVidia, nVidia GeForce GTX 470, OpenCL, Physics, Tesla C1060

February 10, 2015 by hgpu

FIR filtering and AES encryption with OpenCL 2.0

Carter McCardwell, Tuan Dao, Saoni Mukherjee, David Kaeli

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Tags: AES, Computer science, Filtering, Heterogeneous systems, OpenCL, Security

February 9, 2015 by hgpu

Nucleation Studies on Graphics Processing Units

Benjamin J. Block

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Tags: Anisotropy, ATI, ATI Radeon HD 6970, Biology, Chemistry, Differential equations, Ising model, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Physics, Tesla K20, Thesis

February 6, 2015 by hgpu

Cryptography on Graphics Processing Unit: A Survey

Alpha Sarita Barik, Srinivas Mishra, Manoranjan Pradhan

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Tags: ATI, Computer science, CUDA, nVidia, OpenCL, Security, survey

February 6, 2015 by hgpu

Comparison of OpenCL performance on different platforms using VexCL and Blaze

Hammad Mazhar, Dan Negrut

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Tags: AMD Radeon R7 260, ATI, Benchmarking, Computer science, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20

February 6, 2015 by hgpu

Pointer Analysis for Semi-Automatic Code Parallelizers

Ketan Sudhakar Vyavahare

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Tags: Code generation, Computer science, CUDA, OpenCL, Thesis

February 3, 2015 by hgpu

Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism

A Geetha Venkatesh

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Tags: Computer science, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, OpenCL, Tesla C2070, Thesis

February 3, 2015 by hgpu

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

Olivier MELET, Toon Huysmans, Michel Hummel, Pierre-Marie Brunet

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Tags: CUDA, Image processing, Intel Xeon Phi, nVidia, nVidia GeForce GTX 480, OpenCL, Tesla K20

February 3, 2015 by hgpu

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

Hiroyuki Takizawa, Shoichi Hirasawa, Makoto Sugawara, Isaac Gelado, Hiroaki Kobayashi, Wen-mei W. Hwu

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Tags: Computer science, nVidia, nVidia GeForce GTX Titan, OpenCL, Programming techniques, Tesla C1060, Tesla C2070

February 1, 2015 by hgpu

In-Memory Data Analytics on Coupled CPU-GPU Architectures

Jiong He, Bingsheng He, Mian Lu, Shuhao Zhang

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Tags: Algorithms, Computer science, Databases, OpenCL

February 1, 2015 by hgpu

Productive and Efficient Computational Science Through Domain-specific Abstractions

Florian Rathgeber

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, OpenCL, Partial differential equations, PDEs, Thesis

February 1, 2015 by hgpu

OpenCL Implementation of LiDAR Data Processing

Alexander Bussiere

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, nVidia, nVidia GeForce GT 740 M, OpenCL, Robotics, Thesis

January 30, 2015 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

See all packages

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high performance computing on graphics processing units: hgpu.org

CAVE-CL: An OpenCL version of the package for detection and quantitative analysis of internal cavities in a system of overlapping balls: application to proteins

FIR filtering and AES encryption with OpenCL 2.0

Nucleation Studies on Graphics Processing Units

Cryptography on Graphics Processing Unit: A Survey

Comparison of OpenCL performance on different platforms using VexCL and Blaze

Pointer Analysis for Semi-Automatic Code Parallelizers

Exploiting Concurrency Patterns with Heterogeneous Task and Data Parallelism

GPGPU and MIC in Accelerated Cluster for Remote Sensed Image Processing Software

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

In-Memory Data Analytics on Coupled CPU-GPU Architectures

Productive and Efficient Computational Science Through Domain-specific Abstractions

OpenCL Implementation of LiDAR Data Processing

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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