high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Performance Tradeoff Spectrum of Integer and Floating Point Applications

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Tesla C2050, Tesla C2070

May 30, 2013 by hgpu

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Joshua Penton

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Tags: ATI, ATI Radeon HD 6750 M, Computer science, FFT, Java, OpenCL, Package, Performance, Programming techniques

May 28, 2013 by hgpu

Performance Portability in Accelerated Parallel Kernels

John A. Stratton, Hee-Seok Kim, Thoman B. Jablin, Wen-Mei W. Hwu

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

May 27, 2013 by hgpu

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

GEMTC: GPU Enabled Many-Task Computing

Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Performance

May 25, 2013 by hgpu

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Derek R. Hower, Bradford M. Beckmann, Benedict R. Gaster, Blake A. Hechtman, Mark D. Hill, Steven K. Reinhardt, David A. Wood

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

An Investigation of the Performance Portability of OpenCL

S.J. Pennycook, S.D. Hammond, S.A. Wright, J.A. Herdman, I. Miller, S.A. Jarvis

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Tags: ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, Fortran, MPI, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

May 21, 2013 by hgpu

Exploiting Uniform Vector Instructions for GPGPU Performance, Energy Efficiency, and Opportunistic Reliability Enhancement

Ping Xiang, Yi Yang, Mike Mantor, Norm Rubin, Lisa R. Hsu, Huiyang Zhou

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Tags: Computer science, GPGPU-sim, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

May 19, 2013 by hgpu

Parallel Zonal Summations of Large-Scale Species Occurrence Data on Hybrid CPU-GPU Systems

Jianting Zhang, Simin You

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Tags: CUDA, Data parallelism, Earth and Space Sciences, Filtering, Geoscience, nVidia, nVidia Quadro FX 6000, Performance

May 19, 2013 by hgpu

Performance Evaluation of CPU-GPU communication Depending on the Characteristic of Co-Located Workloads

Dongyou Seo, Shin-gyu Kim, Hyeonsang Eom, Heon Y. Yeom

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Tags: CUDA, nVidia, nVidia GeForce GTX 580, Performance

May 17, 2013 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

See all packages

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high performance computing on graphics processing units: hgpu.org

Performance Tradeoff Spectrum of Integer and Floating Point Applications

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Performance Portability in Accelerated Parallel Kernels

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

OpenCL Performance Evaluation on Modern Multi Core CPUs

GEMTC: GPU Enabled Many-Task Computing

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

An Investigation of the Performance Portability of OpenCL

Exploiting Uniform Vector Instructions for GPGPU Performance, Energy Efficiency, and Opportunistic Reliability Enhancement

Parallel Zonal Summations of Large-Scale Species Occurrence Data on Hybrid CPU-GPU Systems

Performance Evaluation of CPU-GPU communication Depending on the Characteristic of Co-Located Workloads

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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