Heterogeneous systems | Page 70

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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

Performance Analysis of a Large Memory Application on Multiple Architectures

P.M.Kogge

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Tags: Benchmarking, Heterogeneous systems, nVidia, nVidia Tesla, Performance

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

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 Portability Evaluation for OpenACC on Intel Knights Corner and Nvidia Kepler

Yichao Wang, Qiang Qin, Simon Chong Wee SEE, James Lin

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Tags: Computer science, Heterogeneous systems, Intel Phi, nVidia, OpenACC, Tesla K20

October 4, 2013 by hgpu

Advanced Optimization Techniques for Sparse Grids on Modern Heterogeneous Systems

Alin Florindor Murarasu

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia Quadro 6000, Thesis

October 4, 2013 by hgpu

Towards Multi-GPU Support in the Marrow Skeleton Framework

Fernando Alexandre, Ricardo Marques, Herve Paulino

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, Heterogeneous systems, nVidia, nVidia Quadro FX 3800, OpenCL, Tesla C1060

October 3, 2013 by hgpu

Exploring Programming Multi-GPUs using OpenMP & OpenACC-based Hybrid Model

Rengan Xu, Sunita Chandrasekaran, Barbara Chapman

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Tags: Computer science, Heterogeneous systems, nVidia, OpenACC, OpenMP, Tesla C2075

September 30, 2013 by hgpu

Separate Compilation in a Language-Integrated Heterogeneous Environment

Mike Murphy, Jaydeep Marathe, Girish Bharambe, Sean Lee, Vinod Grover

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia

September 29, 2013 by hgpu

OpenCL Parallel Programming Development Cookbook

Raymond Tay

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Tags: Book, Computer science, Heterogeneous systems, OpenCL, Tutorial

September 27, 2013 by hgpu

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Guodong Han, Chenggang Zhang, King Tin Lam, Cho-Li Wang

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla M2050

September 27, 2013 by hgpu

Trellis: Portability Across Architectures with a High-level Framework

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050

September 27, 2013 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

Scalable Fast Multipole Methods on Heterogeneous Architecture

Performance Analysis of a Large Memory Application on Multiple Architectures

Enabling the use of Heterogeneous Computing for Bioinformatics

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

Performance Portability Evaluation for OpenACC on Intel Knights Corner and Nvidia Kepler

Advanced Optimization Techniques for Sparse Grids on Modern Heterogeneous Systems

Towards Multi-GPU Support in the Marrow Skeleton Framework

Exploring Programming Multi-GPUs using OpenMP & OpenACC-based Hybrid Model

Separate Compilation in a Language-Integrated Heterogeneous Environment

OpenCL Parallel Programming Development Cookbook

Java with Auto-Parallelization on Graphics Coprocessing Architecture

Trellis: Portability Across Architectures with a High-level Framework

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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