high performance computing on graphics processing units: hgpu.org

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GPU implementations of scheduling heuristics for heterogeneous computing environments

Sergio Nesmachnow, Mauro Canabe

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C1060

December 9, 2011 by hgpu

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Qiang Liu, Wayne Luk

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Performance, Tesla C2070

December 9, 2011 by hgpu

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

Deepak Mathews Panickal

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Tags: ATI, ATI Radeon HD 5470, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Optimization, Tesla C2070, Thesis

December 9, 2011 by hgpu

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Alecio Pedro Delazari Binotto

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, OpenCL, Task scheduling, Thesis

December 5, 2011 by hgpu

Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

G. Arbanas, M.E. Dunn, D. Wiarda

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Tags: CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Matrix multiplication, Nuclear Experiment, nVidia, Physics, Tesla C2050

December 3, 2011 by hgpu

Acceleration of computational quantum chemistry by heterogeneous computer architectures

Yuki Furukawa, Ryota Koga, Koji Yasuda

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, Heterogeneous systems, Molecular modeling, nVidia, nVidia GeForce GTX 580

November 30, 2011 by hgpu

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Jerome Dubois, Christophe Calvin, Serge Petiton

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Tags: Cell processor, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060

November 30, 2011 by hgpu

Multiresolution Flow Simulations on Multi/many-core Architectures

Diego Rossinelli

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Tags: Algorithms, Computational Complexity, CUDA, Differential equations, Fluid dynamics, Heterogeneous systems, nVidia, Partial differential equations, PDEs, Tesla S1070, Tesla T10, Thesis, Wavelet

November 29, 2011 by hgpu

Applications Performance on GPGPUs with the Fermi Architecture

Ahmed Mohamed Hassan Abdalla

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 GS, Performance, Tesla C2050, Tesla M1060, Thesis

November 29, 2011 by hgpu

Enabling Efficient Online Profiling of Homogeneous and Heterogeneous Multicore Systems

Dan Upton

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

November 29, 2011 by hgpu

A Short Note on Gaussian Process Modeling for Large Datasets using Graphics Processing Units

Mark Franey, Pritam Ranjan, Hugh Chipman

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Tags: Computer science, CUDA, Heterogeneous systems, Matrix inversion, nVidia, nVidia GeForce GTX 260, Statistics and Probability

November 26, 2011 by hgpu

Heterogeneous Computing and Load Balancing Techniques for Monte Carlo Simulation in a Distributed Environment

Isha Sanjay Deshpande

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Monte Carlo simulation, nVidia, nVidia Quadro FX 5600, Thesis

November 25, 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

GPU implementations of scheduling heuristics for heterogeneous computing environments

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Computation of Large Covariance Matrices by SAMMY on Graphical Processing Units and Multicore CPUs

Acceleration of computational quantum chemistry by heterogeneous computer architectures

Performance and numerical accuracy evaluation of heterogeneous multicore systems for Krylov orthogonal basis computation

Multiresolution Flow Simulations on Multi/many-core Architectures

Applications Performance on GPGPUs with the Fermi Architecture

Enabling Efficient Online Profiling of Homogeneous and Heterogeneous Multicore Systems

A Short Note on Gaussian Process Modeling for Large Datasets using Graphics Processing Units

Heterogeneous Computing and Load Balancing Techniques for Monte Carlo Simulation in a Distributed Environment

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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