high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

A New Compilation Path: From Python/NumPy to OpenCL

Xunhao Li, Rahul Garg, Jose Nelson Amaral

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Code generation, Compilers, Computer science, nVidia, nVidia GeForce GTX 260, OpenCL, Python

November 26, 2011 by hgpu

TEG: GPU Performance Estimation Using a Timing Model

Junjie Lai, Andre Seznec

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

November 23, 2011 by hgpu

GPU-Based Image Processing Use Cases: A High-Level Approach

Volkmar Wieser, Clemens Grelck, Holger Schoner, Peter Haslinger, Karoly Bosa, Bernhard Moser

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Tags: Benchmarking, CUDA, Image processing, nVidia, nVidia GeForce GT 425 M, Software Engineering, Virtualization

November 21, 2011 by hgpu

Challenge benchmarks that must be conquered to sustain the gpu revolution

Emily Blem, Matthew Sinclair, Karthikeyan Sankaralingam

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Tags: Benchmarking, Computer science, CUDA, nVidia, Tesla C1060

November 21, 2011 by hgpu

Autotuning GEMMs for Fermi

Jakub Kurzak, Stanimire Tomov, Jack Dongarra

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Tags: Benchmarking, BLAS, Computer science, CUDA, Linear Algebra, Mathematical Software, Matrix multiplication, nVidia, Package, Tesla S2050

November 20, 2011 by hgpu

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

Matthieu Ospici, Dimitri Komatitsch, Jean-Francois Mehaut, Thierry Deutsch

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Tags: Benchmarking, Computer science, CUDA, Hybrid computing, nVidia, Tesla T10

November 19, 2011 by hgpu

Predictive Modeling and Analysis of OP2 on Distributed Memory GPU Clusters

G.R. Mudalige, M.B. Giles, C. Bertolli, P.H.J Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 560 Ti, Performance, Tesla C2070

November 19, 2011 by hgpu

Fast Gather-based Construction of Stereoscopic Images Using Reprojection

Marries van de Hoef, Bas Zalmstra

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Tags: ATI, ATI Radeon HD 5670, ATI Radeon HD 5850, Benchmarking, Cg, Image processing, nVidia, nVidia GeForce 9600 GT, OpenGL, Package

November 18, 2011 by hgpu

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Allen D. Malony, Scott Biersdorff, Sameer Shende, Heike Jagode, Stanimire Tomov, Guido Juckeland, Robert Dietrich, Duncan Poole, Christopher Lamb

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C870

November 17, 2011 by hgpu

Prospects for scalable 3D FFTs on heterogeneous exascale systems

Chris McClanahan, Kent Czechowski, Casey Battaglino, Kartik Iyer, P.-K. Yeung, Richard Vuduc

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Tags: Analytical model, Benchmarking, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Tesla M2070

November 16, 2011 by hgpu

An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Algorithms, Benchmarking, Biology, CUDA, GPU cluster, MPI, nVidia, OpenMP, Package, Tesla S2050

November 15, 2011 by hgpu

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data parallelism, GPU cluster, nVidia, Tesla C2050

November 15, 2011 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

A New Compilation Path: From Python/NumPy to OpenCL

TEG: GPU Performance Estimation Using a Timing Model

GPU-Based Image Processing Use Cases: A High-Level Approach

Challenge benchmarks that must be conquered to sustain the gpu revolution

Autotuning GEMMs for Fermi

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

Predictive Modeling and Analysis of OP2 on Distributed Memory GPU Clusters

Fast Gather-based Construction of Stereoscopic Images Using Reprojection

Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

Prospects for scalable 3D FFTs on heterogeneous exascale systems

An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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