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Fast Algorithms for Convolutional Neural Networks

Andrew Lavin

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Tags: Algorithms, CNN, Computer science, Deep learning, FFT, Image recognition, Machine learning, Neural networks

October 3, 2015 by hgpu

Brute-Force k-Nearest Neighbors Search on the GPU

Shengren Li, Nina Amenta

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Tags: Computer science, CUDA, Matrix multiplication, Nearest neighbour, nVidia, nVidia GeForce GTX 460, Sorting

October 3, 2015 by hgpu

Analysis of A Splitting Approach for the Parallel Solution of Linear Systems on GPU Cards

Ang Li, Radu Serban, Dan Negrut

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Package, Sparse direct solvers, Tesla K20

September 30, 2015 by hgpu

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Shuoxin Lin

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Tags: Benchmarking, Computer science, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Thesis

September 29, 2015 by hgpu

Solving prime-field ECDLPs on GPUs with OpenCL

Erik Boss

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Tags: ATI, ATI Radeon HD 7850, Computer science, nVidia, nVidia GeForce GTX 780, OpenCL, Security, Thesis

September 29, 2015 by hgpu

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kim, Hadi Esmaeilzadeh

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Tags: ARM, ASIC, Computer science, FPGA, Machine learning, nVidia, nVidia GeForce GTX 650 Ti, nVidia Jetson TK1, Performance, Tesla K40

September 29, 2015 by hgpu

Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic

Mujeeb B Jimoh

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan, Security, Thesis

September 29, 2015 by hgpu

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

John-Alexander M. Assael

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Tags: CNN, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Tesla K40, Thesis

September 26, 2015 by hgpu

Efficient Simulation Techniques for Large-Scale Applications

Jen-Cheng Huang

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Tags: Analytical model, Computer science, CUDA, nVidia, nVidia Quadro 6000, Performance, Thesis

September 26, 2015 by hgpu

Fast Exact Bayesian Inference for High-Dimensional Models

Joao Filipe Ferreira, Pablo Lanillos, Jorge Dias

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Tags: Bayesian, Computer science, Computer vision, nVidia, nVidia GeForce GTX 780, OpenCL, Robotics

September 26, 2015 by hgpu

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

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Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 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

Fast Algorithms for Convolutional Neural Networks

Brute-Force k-Nearest Neighbors Search on the GPU

Analysis of A Splitting Approach for the Parallel Solution of Linear Systems on GPU Cards

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Solving prime-field ECDLPs on GPUs with OpenCL

TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning

Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

Efficient Simulation Techniques for Large-Scale Applications

Fast Exact Bayesian Inference for High-Dimensional Models

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

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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