high performance computing on graphics processing units: hgpu.org

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Fast and Efficient Automatic Memory Management for GPUs using Compiler-Assisted Runtime Coherence Scheme

Sreepathi Pai, R. Govindarajan, Matthew J. Thazhuthaveetil

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Tags: Computer science, CUDA, Memory model, nVidia, Performance, Tesla C1060

September 21, 2012 by hgpu

Parallel Benefit on Different Programming Paradigms

Chau-Yi Chou, Sheng-Hsiu Kuo, Chih-Wei Hsieh, Tsung-Che Tsai, Hsi-Ya Chang

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GT 200, OpenMP, Performance

September 16, 2012 by hgpu

Medusa: Simplified Graph Processing on GPUs

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Optimization, Performance, Tesla C2050

September 12, 2012 by hgpu

Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

Yusuke Shimotoku, Toshiaki Tanaka, Ryuichi Itoi

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2070

September 10, 2012 by hgpu

Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

Prabhakar Misra, Mainak Chaudhuri

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, Performance, Tesla C2070

September 8, 2012 by hgpu

Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

Benedict R. Gaster, Lee Howes

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Performance

September 7, 2012 by hgpu

Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking

Saktheesh Subramoniapillai Ajeetha

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Performance, Tesla C2050, Thesis

September 6, 2012 by hgpu

Automated Enhanced Parallelization of Sequential C to Parallel OpenMP

Dheeraj D., Shruti Ramesh, Nitish B.

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Tags: Computer science, MPI, OpenMP, Performance

September 4, 2012 by hgpu

Parallel Data List Processing on Multicore-GPU Platforms

Carlos Alberto Martinez-Angeles, Jorge Buenabad-Chavez, Miguel Alfonso Castro-Garcia, Jose Luis Quiroz-Fabian

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 460, Performance

August 30, 2012 by hgpu

GPUVerify: A Verifier for GPU Kernels

Adam Betts, Nathan Chong, Alastair F. Donaldson, Shaz Qadeer, Paul Thomson

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Tags: ARM, ATI, ATI Radeon HD 7970, Code generation, Computer science, CUDA, nVidia, OpenCL, Package, Performance, Tesla C2050

August 28, 2012 by hgpu

Performance Comparison Between Cg-based and CUDA-based Matrix Multiplications

Luke West, Jong Kwan Lee

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Tags: Cg, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

August 28, 2012 by hgpu

Optimization Techniques for CUDA Application

Tushar Athawale, Xie Xu

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Performance

August 28, 2012 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

Fast and Efficient Automatic Memory Management for GPUs using Compiler-Assisted Runtime Coherence Scheme

Parallel Benefit on Different Programming Paradigms

Medusa: Simplified Graph Processing on GPUs

Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

Can GPGPU Programming Be Liberated from the Data-Parallel Bottleneck?

Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking

Automated Enhanced Parallelization of Sequential C to Parallel OpenMP

Parallel Data List Processing on Multicore-GPU Platforms

GPUVerify: A Verifier for GPU Kernels

Performance Comparison Between Cg-based and CUDA-based Matrix Multiplications

Optimization Techniques for CUDA Application

Recent source codes

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

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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