high performance computing on graphics processing units: hgpu.org

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hgpu.org » Programming » OpenCL

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

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Yi Yang, Ping Xiang, Jingfei Kong, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Optimization, Package, Programming Languages

August 27, 2012 by hgpu

Rootbeer: Seamlessly using GPUs from Java

Philip C. Pratt-Szeliga, James W. Fawcett, Roy D. Welch

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Tags: Code generation, Computer science, CUDA, Java, nVidia, OpenCL, Package, Tesla C2050

August 17, 2012 by hgpu

accULL: An User-directed Approach to Heterogeneous Programming

Ruyman Reyes, Ivan Lopez, Juan J. Fumero, Francisco de Sande

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Python, Tesla C1060, Tesla C2050

July 31, 2012 by hgpu

Ensemble K-Means on Modern Many Core Hardware

Girish Ravunnikutty

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Tags: Bioinformatics, Clustering, Computer science, Data mining, Machine learning, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Pattern recognition, Thesis

July 28, 2012 by hgpu

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Jungwon Kim, Sangmin Seo, Jun Lee, Jeongho Nah, Gangwon Jo, Jaejin Lee

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Tags: Code generation, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package, Programming Languages, Programming techniques

July 26, 2012 by hgpu

Geometric Algebra enhanced Precompiler for C++ and OpenCL

Patrick Charrier, Dietmar Hildenbrand

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, Programming techniques

July 11, 2012 by hgpu

A fully parallel, high precision, N-body code running on hybrid computing platforms

R. Capuzzo-Dolcetta, M. Spera, D. Punzo

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, Computational Physics, Gravitation, Hybrid computing, Instrumentation and Methods for Astrophysics, MPI, N-body simulation, nVidia, OpenCL, Package, Tesla M2070

July 11, 2012 by hgpu

Utilizing GPGPU in Computer Emulation

Peter Jakubco, Slavomir Simonak

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Tags: ATI, ATI Radeon HD 6570, Computer science, OpenCL, Package

July 8, 2012 by hgpu

Automatic Optimization of In-Flight Memory Transactions for GPU Accelerators based on a Domain-Specific Language for Medical Imaging

Richard Membarth, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: Code generation, CUDA, Image processing, nVidia, OpenCL, Optimization, Package, Tesla C2050

July 3, 2012 by hgpu

GPU Computing: Image Convolution

Jan Novak, Anton Kaplanyan, Gabor Liktor, Carsten Dachsbacher

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Tags: Education, Image processing, OpenCL, Package

June 20, 2012 by hgpu

S-buffer: Sparsity-aware Multi-fragment Rendering

Andreas A. Vasilakis, Ioannis Fudos

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Tags: Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, OpenGL, Package, Rendering

June 10, 2012 by hgpu

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

Programming

GPUVerify: A Verifier for GPU Kernels

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Rootbeer: Seamlessly using GPUs from Java

accULL: An User-directed Approach to Heterogeneous Programming

Ensemble K-Means on Modern Many Core Hardware

SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters

Geometric Algebra enhanced Precompiler for C++ and OpenCL

A fully parallel, high precision, N-body code running on hybrid computing platforms

Utilizing GPGPU in Computer Emulation

Automatic Optimization of In-Flight Memory Transactions for GPU Accelerators based on a Domain-Specific Language for Medical Imaging

GPU Computing: Image Convolution

S-buffer: Sparsity-aware Multi-fragment Rendering

Recent source codes

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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