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Face Retriever: Pre-filtering the Gallery via Deep Neural Net

Dayong Wang, Anil K. Jain

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Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, Filtering, Machine learning, Neural networks, nVidia, Tesla K20

March 30, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

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Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

Guillaume Chapuis, Hristo Djidjev

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Tags: Computer science, Data Structures and Algorithms, Distributed computing, Distributed data structures, GPU cluster, nVidia, Path problems, Tesla M2090

March 28, 2015 by hgpu

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Xiaowen Chu, Chengjian Liu, Kai Ouyang, Ling Sing Yung, Hai Liu, Yiu-Wing Leung

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Tags: Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 780

March 28, 2015 by hgpu

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Vadim Demchik

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 560 M, nVidia GeForce GTX 780, OpenCL, Package, Pseudo-random number generators, Review, Tesla K40

March 25, 2015 by hgpu

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Cluster computing, Computer science, CUDA, Distributed computing, Energy-efficient computing, GPU cluster, nVidia, Tesla K20

March 25, 2015 by hgpu

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Kamran Karimi

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Tags: ATI, Computer science, OpenCL, OpenMP, Performance

March 25, 2015 by hgpu

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Yuki Tsujita, Toshio Endo

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Tags: Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Task scheduling, Tesla K20

March 25, 2015 by hgpu

Curracurrong: a stream processing system for distributed environments

Vasvi Kakkad

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Tags: Algorithms, Computer science, CUDA, OpenCL, Thesis

March 23, 2015 by hgpu

Massively Parallel Construction of the Cell Graph

Krzysztof Kaczmarski, Pawel Rzazewski, Albert Wolant

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Tags: Algorithms, Computer science, CUDA, nVidia, Robotics, Tesla K40

March 23, 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

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high performance computing on graphics processing units: hgpu.org

Applications

Face Retriever: Pre-filtering the Gallery via Deep Neural Net

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Loo.py: From Fortran to performance via transformation and substitution rules

Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures

PErasure: a Parallel Cauchy Reed-Solomon Coding Library for GPUs

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Curracurrong: a stream processing system for distributed environments

Massively Parallel Construction of the Cell Graph

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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