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Visualization of OpenCL Application Execution on CPU-GPU Systems

Amir Kavyan Ziabari, Rafael Ubal, Dana Schaa, David Kaeli

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Tags: ARM, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Visualization

June 19, 2015 by hgpu

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Adrian Castello, Rafael Mayo, Enrique S. Quintana-Orti, Antonio J. Pena, Pavan Balaji

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Tesla C2050, Tesla K40, Virtualization

June 17, 2015 by hgpu

Automatic Data Layout Optimizations for GPUs

Klaus Kofler, Biagio Cosenza, Thomas Fahringer

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Tags: Algorithms, AMD FirePro S9000, ATI, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, OpenCL, Optimization, Tesla K20

June 17, 2015 by hgpu

Layered Interpretation of Street View Images

Ming-Yu Liu, Shuoxin Lin, Srikumar Ramalingam, Oncel Tuzel

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Tags: Algorithms, Computer science, Computer vision, CUDA, Neural networks, nVidia, Robotics, Tesla K40, Vehicular traffic

June 17, 2015 by hgpu

Perfect Hashing Structures for Parallel Similarity Searches

Tuan Tu Tran, Mathieu Giraud, Jean-Stephane Varre

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Tags: Algorithms, Computer science, Databases, Filtering, Hashing, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan, OpenCL

June 16, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

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Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 by hgpu

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

N. Sedaghati, A. Ashari, L. N. Pouchet, S. Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla K40

June 16, 2015 by hgpu

GPU Predictor-Corrector Interior Point Method for Large-Scale Linear Programming

David Rydberg

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Thesis

June 16, 2015 by hgpu

Automatic Selection of Sparse Matrix Representation on GPUs

Naser Sedaghati, Te Mu, Louis-Noel Pouchet, Srinivasan Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Physics, Sparse matrix, Tesla K20, Tesla K40

June 14, 2015 by hgpu

Type-safe Runtime Code Generation: Accelerate to LLVM

Trevor L. McDonell, Manuel M. T. Chakravarty, Vinod Grover, Ryan R. Newton

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Sparse matrix, Tesla K40

June 14, 2015 by hgpu

Accelerating parameter synthesis for stochastic models

Petr Pilar

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Probability, Sparse matrix, Thesis

June 14, 2015 by hgpu

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Peng Li

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

June 10, 2015 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

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high performance computing on graphics processing units: hgpu.org

Applications

Visualization of OpenCL Application Execution on CPU-GPU Systems

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model Using rCUDA

Automatic Data Layout Optimizations for GPUs

Layered Interpretation of Street View Images

Perfect Hashing Structures for Parallel Similarity Searches

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

GPU Predictor-Corrector Interior Point Method for Large-Scale Linear Programming

Automatic Selection of Sparse Matrix Representation on GPUs

Type-safe Runtime Code Generation: Accelerate to LLVM

Accelerating parameter synthesis for stochastic models

Practical Symbolic Execution Analysis and Methodology for GPU Programs

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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