high performance computing on graphics processing units: hgpu.org

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SHADOW3 API: The Application Programming Interface for the ray tracing code SHADOW

Niccolo Canestrari, Dimitris Karkoulis, Manuel Sanchez del Rio

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Tags: Code generation, Computer science, Fortran, nVidia, OpenCL, Python, Raytracing, Tesla M2050

December 26, 2011 by hgpu

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Qi Li

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Optimization, Sorting, Tesla C1060, Tesla C2050, Tesla C2070, Thesis

December 26, 2011 by hgpu

Sparse matrix-vector multiplication on GPGPU clusters: A new storage format and a scalable implementation

Moritz Kreutzer, Georg Hager, Gerhard Wellein, Holger Fehske, Achim Basermann, Alan R. Bishop

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Tags: Computer science, GPU cluster, nVidia, Performance, Sparse matrix, Tesla C2050, Tesla C2070

December 26, 2011 by hgpu

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Changkyu Kim, Jatin Chhugani, Nadathur Satish, Eric Sedlar, Anthony D. Nguyen, Tim Kaldewey, Victor W. Lee, Scott A. Brandt, Pradeep Dubey

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Tags: Compression, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 280, Search, Tesla C2050

December 25, 2011 by hgpu

Turbo Bayesian Compressed Sensing

Depeng Yang

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Tags: Algorithms, Bayesian, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 480, Sensing, Signal processing

December 25, 2011 by hgpu

Modeling Parallel Programs for Heterogeneous Computing

Ferosh Jacob

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance

December 25, 2011 by hgpu

Methodology of control and supervision of web connected mobile robots with CUDA technology application

Janusz Bedkowski, Andrzej Maslowski

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, nVidia Quadro FX 1600 M, nVidia Quadro FX 3700

December 25, 2011 by hgpu

Accelerating linear system solutions using randomization techniques

Marc Baboulin, Jack Dongarra, Julien Herrmann, Stanimire Tomov

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

December 25, 2011 by hgpu

G-CP: Providing Fault Tolerance on the GPU through Software Checkpointing

Felix Loh, Matt Sinclair

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Tags: Algorithms, Computer science, CUDA, Fault tolerance, nVidia, Tesla C1060

December 25, 2011 by hgpu

Design and Development of Optical Flow Based Obstacle Avoidance Using CUDA

S. Jeevith , N.D. Gangadhar, S. Santhosh Kumar

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Optical flow

December 25, 2011 by hgpu

Toolchain for programming, simulating and studying the XMT many-core architecture

Fuat Keceli, Alexandros Tzannes, George C. Caragea, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, Compilers, Computer science, Hardware Architecture, nVidia, nVidia GeForce GTX 280, Package

December 24, 2011 by hgpu

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Duane Merrill, Andrew Grimshaw

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Sorting

December 24, 2011 by hgpu

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

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

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

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high performance computing on graphics processing units: hgpu.org

SHADOW3 API: The Application Programming Interface for the ray tracing code SHADOW

Fast Parallel Machine Learning Algorithms for Large Datasets Using Graphic Processing Unit

Sparse matrix-vector multiplication on GPGPU clusters: A new storage format and a scalable implementation

Designing Fast Architecture Sensitive Tree Search on Modern Multi-Core/Many-Core Processors

Turbo Bayesian Compressed Sensing

Modeling Parallel Programs for Heterogeneous Computing

Methodology of control and supervision of web connected mobile robots with CUDA technology application

Accelerating linear system solutions using randomization techniques

G-CP: Providing Fault Tolerance on the GPU through Software Checkpointing

Design and Development of Optical Flow Based Obstacle Avoidance Using CUDA

Toolchain for programming, simulating and studying the XMT many-core architecture

High Performance and Scalable Radix Sorting: A case study of implementing dynamic parallelism for GPU computing

Recent source codes

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

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

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

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

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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