high performance computing on graphics processing units: hgpu.org

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Autotuning Tensor Contraction Computations on GPUs

Axel Rivera, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Thomas Nelson, Boyana Norris

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Tags: Benchmarking, Code generation, Computer science, CUDA, Matrix multiplication, nVidia, OpenACC, Tesla C2050, Tesla K20

June 19, 2015 by hgpu

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Peng Li

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

June 10, 2015 by hgpu

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Thomas L. Falch, Anne C. Elster

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, OpenCL, Tesla K40

June 5, 2015 by hgpu

Genetically Improved BarraCUDA

W. B. Langdon, Brian Yee Hong Lam

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Tags: Algorithms, Benchmarking, Biology, CUDA, Genomics, nVidia, nVidia GeForce GT 730, Package, Tesla K20, Tesla K40, Tesla K80

June 1, 2015 by hgpu

Particle-in-Cell Laser-Plasma Simulation on Xeon Phi Coprocessors

I.A. Surmin, S.I. Bastrakov, E.S. Efimenko, A.A. Gonoskov, A.V. Korzhimanov, I.B. Meyerov

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Tags: Benchmarking, Computational Physics, Intel Xeon Phi, Particle-in-cell methods, Physics, Plasma physics

May 28, 2015 by hgpu

Key derivation functions and their GPU implementation

Ondrej Mosnacek

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Tags: Benchmarking, Computer science, nVidia, OpenCL, Package, Security, Tesla K20, Thesis

May 22, 2015 by hgpu

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Geoffrey Ndu, Javier Navaridas, Mikel Lujan

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package, Performance

May 19, 2015 by hgpu

Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves

Tobias Domhan, Jost Tobias Springenberg, Frank Hutter

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan

May 15, 2015 by hgpu

Age and Gender Classification using Convolutional Neural Networks

Gil Levi, Tal Hassner

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Neural networks, nVidia

May 10, 2015 by hgpu

A Parallel Tree Pattern Query Processing Algorithm for Graph Databases using a GPGPU

Lila Shnaiderman, Oded Shmueli

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

April 14, 2015 by hgpu

Benchmarking the cost of thread divergence in CUDA

Piotr Bialas, Adam Strzelecki

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 610, nVidia GeForce GT 755 M, nVidia GeForce GTX 480, nVidia GeForce GTX 650 M, nVidia GeForce GTX 770, nVidia GeForce GTX 850 M, Performance

April 8, 2015 by hgpu

A Financial Benchmark for GPGPU Compilation

Christian Andreetta, Vivien Begot, Jost Berthold, Martin Elsman, Troels Henriksen, Maj-Britt Nordfang, Cosmin E. Oancea

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Tags: Benchmarking, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780 Ti

March 23, 2015 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

Autotuning Tensor Contraction Computations on GPUs

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Machine Learning Based Auto-tuning for Enhanced OpenCL Performance Portability

Genetically Improved BarraCUDA

Particle-in-Cell Laser-Plasma Simulation on Xeon Phi Coprocessors

Key derivation functions and their GPU implementation

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves

Age and Gender Classification using Convolutional Neural Networks

A Parallel Tree Pattern Query Processing Algorithm for Graph Databases using a GPGPU

Benchmarking the cost of thread divergence in CUDA

A Financial Benchmark for GPGPU Compilation

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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