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Reducing the Disk IO Bandwidth Bottleneck through Fast Floating Point Compression using Accelerators

Ajith Padyana, Devi Sudheer, Pallav Kumar Baruah, Ashok Srinivasan

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Tags: Algorithms, Cell processor, Compression, Computer science, CUDA, nVidia, Tesla M2050

April 9, 2014 by hgpu

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Zheng Xia

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Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Review

April 9, 2014 by hgpu

Exploring the power of GPU’s for training Deep Belief Networks

Vivek Kulkarni

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 570

April 9, 2014 by hgpu

A New Non-Blocking Approach on GPU Dynamical Memory Management

Yu-Shiang Lin, Chun-Yuan Lin, Jon-Yu Lee

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Tags: Computer science, CUDA, Memory model, nVidia, Performance, Tesla K20

April 7, 2014 by hgpu

A New Digital Repository for Hyperspectral Imagery with Unmixing-Based Retrieval Functionality Implemented on GPUs

Jorge Sevilla, Antonio Plaza

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Tags: CUDA, Image processing, nVidia, Sensing, Tesla C2050

April 7, 2014 by hgpu

Detection of a faint fast-moving near-Earth asteroid using synthetic tracking technique

Chengxing Zhai, Michael Shao, Bijan Nemati, Thomas Werne, Hanying Zhou, Slava G. Turyshev, Jagmit Sandhu, Gregg W. Hallinan, Leon K. Harding

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Tags: Astrophysics, CUDA, Earth and Planetary Astrophysics, Instrumentation and Methods for Astrophysics, nVidia, Tesla K20

April 7, 2014 by hgpu

A Study on Efficient Application Mapping on Parallel Computing Accelerators

Keisuke Dohi

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Tags: Algorithms, Computer science, CUDA, FDTD, Finite-difference time-domain, FPGA, MPI, nVidia, nVidia GeForce GTX 295, Smith-Waterman algorithm, Thesis

April 7, 2014 by hgpu

Parallel processing for SAR image generation in CUDA – GPGPU platform

Prajakta Tapkir, Saurabh Thakur, C. Bhattacharya

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Tags: Algorithms, CUDA, Image generation, nVidia, nVidia Quadro FX 1800, Signal processing, Tesla C870

April 7, 2014 by hgpu

Acceleration of a Full-scale Industrial CFD Application with OP2

Istvan Z. Reguly, Gihan R. Mudalige, Carlo Bertolli, Michael B. Giles, Adam Betts, Paul H. J. Kelly, David Radford

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Tags: Computer science, CUDA, Fluid dynamics, MPI, nVidia, Performance, Tesla K20

April 7, 2014 by hgpu

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Hartwig Anzt, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Sorting, Sparse matrix, Tesla K40

April 7, 2014 by hgpu

Optimizing Krylov Subspace Solvers on Graphics Processing Units

Hartwig Anzt, Stanimire Tomov, Piotr Luszczek, Ichitaro Yamazaki, Jack Dongarra, William Sawyer

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla K20

April 6, 2014 by hgpu

A Low-Power Hybrid CPU-GPU Sort

Lawrence Tan

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia ION, Sorting, Thesis

April 6, 2014 by hgpu

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

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Reducing the Disk IO Bandwidth Bottleneck through Fast Floating Point Compression using Accelerators

Literature Review: Parallel Computing on linear equations of linear elastic FEM stimulation with CUDA

Exploring the power of GPU’s for training Deep Belief Networks

A New Non-Blocking Approach on GPU Dynamical Memory Management

A New Digital Repository for Hyperspectral Imagery with Unmixing-Based Retrieval Functionality Implemented on GPUs

Detection of a faint fast-moving near-Earth asteroid using synthetic tracking technique

A Study on Efficient Application Mapping on Parallel Computing Accelerators

Parallel processing for SAR image generation in CUDA – GPGPU platform

Acceleration of a Full-scale Industrial CFD Application with OP2

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Optimizing Krylov Subspace Solvers on Graphics Processing Units

A Low-Power Hybrid CPU-GPU Sort

Recent source codes

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

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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

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