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Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Blesson Varghese, Andrew Rau-Chaplin

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Tags: Computational Engineering, Computer science, CUDA, Finance, nVidia, Risk Management, Tesla C2075

October 10, 2013 by hgpu

Scalable Fast Multipole Methods on Heterogeneous Architecture

Q. Hu

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla C1060, Tesla C2050, Thesis

October 9, 2013 by hgpu

Enabling the use of Heterogeneous Computing for Bioinformatics

Ramakrishna Bijanapalli Chakri

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Smith-Waterman algorithm, Thesis

October 8, 2013 by hgpu

Stressing the BER simulation of LDPC codes in the error floor region using GPU clusters

Gabriel Falcao, Joao Andrade, Vitor Silva, Shinichi Yamagiwa, Leonel Sousa

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Tags: Computer science, CUDA, GPU cluster, Monte Carlo simulation, nVidia, Parity-check codes, Tesla M2050

October 8, 2013 by hgpu

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

Charalampos S. Kouzinopoulos

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 280, String matching, Thesis

October 8, 2013 by hgpu

libcloudph++ 0.1: single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

Sylwester Arabas, Anna Jaruga, Hanna Pawlowska, Wojciech W. Grabowski

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Tags: Algorithms, CUDA, Earth and Space Sciences, nVidia, nVidia Quadro 600, Package, Physics, Thrust

October 8, 2013 by hgpu

Porting Large HPC Applications to GPU Clusters: The Codes GENE and VERTEX

Tilman Dannert, Andreas Marek, Markus Rampp

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Tags: Computational Physics, CUDA, GPU cluster, Heterogeneous systems, nVidia, PC cluster, Physics, Plasma physics, Solar and Stellar Astrophysics, Tesla K20

October 8, 2013 by hgpu

Performance evaluation of CUDA programming for machining simulation

Felix Abecassis, Sylvain Lavernhe, Christophe Tournier, Pierre-Alain Boucard

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Tags: Computer science, CUDA, nVidia, nVidia Quadro 4000, Physics

October 7, 2013 by hgpu

GPU Accelerated Conjunction Assessment with Applications to Formation Flight and Space Debris Tracking

Abel Brown, Jason Tichy, Michael Demoret, David Rand

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Tags: CUDA, Earth and Space Sciences, nVidia, Tesla M2050

October 7, 2013 by hgpu

Measurements of performance of hardware and general purpose classical molecular dynamics simulation software

Jose O. Sotero-Esteva

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Tags: CUDA, Molecular dynamics, nVidia, Physics, Tesla C2075

October 5, 2013 by hgpu

Parametric GPU Code Generation for Affine Loop Programs

Athanasios Konstantinidis, Paul H. J. Kelly, J. Ramanujam, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 580, OpenCL, Package, Tesla K20, Tesla M2070

October 5, 2013 by hgpu

Facial Expression Recognition – Review

Umesh Balkrishna Chavan, Dinesh B Kulkarni

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Tags: Computer science, Computer vision, CUDA, nVidia, Pattern recognition

October 4, 2013 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

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high performance computing on graphics processing units: hgpu.org

Programming

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Scalable Fast Multipole Methods on Heterogeneous Architecture

Enabling the use of Heterogeneous Computing for Bioinformatics

Stressing the BER simulation of LDPC codes in the error floor region using GPU clusters

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

libcloudph++ 0.1: single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

Porting Large HPC Applications to GPU Clusters: The Codes GENE and VERTEX

Performance evaluation of CUDA programming for machining simulation

GPU Accelerated Conjunction Assessment with Applications to Formation Flight and Space Debris Tracking

Measurements of performance of hardware and general purpose classical molecular dynamics simulation software

Parametric GPU Code Generation for Affine Loop Programs

Facial Expression Recognition – Review

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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