high performance computing on graphics processing units: hgpu.org

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Classification of Higgs Boson Tau-Tau decays using GPU accelerated Neural Networks

Mohit Shridhar

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Tags: CUDA, Deep learning, High Energy Physics - Phenomenology, Machine learning, Neural networks, nVidia, Physics

January 14, 2016 by hgpu

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Alessio Sclocco, Joeri van Leeuwen, Henri E. Bal, Rob V. van Nieuwpoort

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Tags: Astrophysics, ATI, ATI Radeon HD 7970, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce Titan, OpenCL, OpenMP, Package, Tesla K20

January 12, 2016 by hgpu

GPU Remote Memory Access Programming

Jeremia Bar

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, OpenMPI, Tesla K80, Thesis

January 12, 2016 by hgpu

A Workload Balanced MapReduce Framework on GPU Platforms

Yue Zhang

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Tags: Benchmarking, Computer science, CUDA, MapReduce, nVidia, Performance, Tesla K40, Thesis

January 12, 2016 by hgpu

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Mishal Almazrooie, Mogana Vadiveloo, Rosni Abdullah

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla C2050

January 7, 2016 by hgpu

Computationally Efficient Tsunami Modelling on Graphics Processing Units (GPU)

Reza Amouzgar, Qiuhua Liang, Peter J. Clarke, Tomohiro Yasuda, Hajime Mase

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Tags: CUDA, Earth and Space Sciences, Fluid dynamics, nVidia, Tesla M2075

January 7, 2016 by hgpu

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

Phillipe A. Pereira, Higo F. Albuquerque, Hendrio M. Marques, Isabela S. Silva, Celso B. Carvalho, Lucas C. Cordeiro

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Tags: Computer science, CUDA, nVidia, Package

January 7, 2016 by hgpu

Faster GPU Based Genetic Programming Using A Two Dimensional Stack

Darren M. Chitty

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 670

January 7, 2016 by hgpu

Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Judit Planas Carbonell

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OmpSs, Task scheduling, Tesla K20, Tesla K40, Tesla M2090, Thesis

January 4, 2016 by hgpu

Automatic Performance Tuning of Stencil Computations on Graphics Processing Units

Joseph D. Garvey

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Tags: Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Stencil computation, Thesis

January 4, 2016 by hgpu

CUDA Parallel Algorithms for Forward and Inverse Structural Gravity Problems

Alexander Tsidaev

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Tags: CUDA, Earth and Space Sciences, Geoscience, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780 Ti, Tesla M2050

January 4, 2016 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

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high performance computing on graphics processing units: hgpu.org

Classification of Higgs Boson Tau-Tau decays using GPU accelerated Neural Networks

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

GPU Remote Memory Access Programming

A Workload Balanced MapReduce Framework on GPU Platforms

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Computationally Efficient Tsunami Modelling on Graphics Processing Units (GPU)

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

Faster GPU Based Genetic Programming Using A Two Dimensional Stack

Batched Linear Algebra Problems on GPU Accelerators

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Automatic Performance Tuning of Stencil Computations on Graphics Processing Units

CUDA Parallel Algorithms for Forward and Inverse Structural Gravity Problems

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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