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Efficient Kernel Fusion Techniques for Massive Video Data Analysis on GPGPUs

Asif M Adnan, Sridhar Radhakrishnan, Suleyman Karabuk

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Tags: Algorithms, CUDA, Image processing, Neuroscience, nVidia, nVidia GeForce GTX 750 Ti, Tesla C1060, Tesla K20

September 17, 2015 by hgpu

SKMD: Single Kernel on Multiple Devices for Transparent CPU-GPU Collaboration

Janghaeng Lee, Mehrzad Samadi, Yongjun Park, Scott Mahlke

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 760, OpenCL

September 17, 2015 by hgpu

CLTune: A Generic Auto-Tuner for OpenCL Kernels

Cedric Nugteren, Valeriu Codreanu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel HD 5100, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Performance, Tesla K40

September 17, 2015 by hgpu

gSLICr: SLIC superpixels at over 250Hz

Carl Yuheng Ren, Victor Adrian Prisacariu, Ian D Reid

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Tags: Clustering, Computer science, Computer vision, CUDA, nVidia, OpenCV, Package

September 17, 2015 by hgpu

Scalable Metropolis Monte Carlo for simulation of hard shapes

Joshua A. Anderson, M. Eric Irrgang, Sharon C. Glotzer

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Tags: Benchmarking, Chemistry, Condensed matter, CUDA, Monte Carlo simulation, nVidia, Physics, Soft Condensed Matter, Tesla K20

September 17, 2015 by hgpu

linalg: Matrix Computations in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Sparks, Alexander Ulanov, Matei Zaharia

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Linear Algebra, Machine learning, Matrix multiplication, nVidia, Package, Scala, Tesla M2050

September 15, 2015 by hgpu

Refinements in Syntactic Parsing

David Hall

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, Scala, Thesis

September 15, 2015 by hgpu

PENCIL: A Platform-Neutral Compute Intermediate Language for Accelerator Programming

Riyadh Baghdadi, Ulysse Beaugnon, Albert Cohen, Tobias Grosser, Michael Kruse, Chandan Reddy, Sven Verdoolaege, Adam Betts, Alastair F. Donaldson, Jeroen Ketema, Javed Absar, Sven van Haastregt, Alexey Kravets, Anton Lokhmotov, Robert David, Elnar Hajiyev

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Tags: AMD Radeon R9 285, ARM, ATI, Computer science, DSL, High-level Languages, Image processing, Linear Algebra, nVidia, nVidia GeForce GTX 470, OpenCL, Package, Signal processing

September 15, 2015 by hgpu

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Fabian Tschopp

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Tags: AMD FirePro W9100, Artificial intelligence, ATI, Caffe, CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Thesis

September 15, 2015 by hgpu

A GPU-based Parallel Ant Colony Algorithm for Scientific Workflow Scheduling

Pengfei Wang, Huifang Li, Baihai Zhang

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Tags: Algorithms, Ant colony optimization, Computer science, CUDA, nVidia, Tesla M2070

September 15, 2015 by hgpu

Three storage formats for sparse matrices on GPGPUs

Davide Barbieri, Valeria Cardellini, Alessandro Fanfarillo, Salvatore Filippone

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 660, Package, Sparse matrix, Tesla M2070

September 9, 2015 by hgpu

Experimentation Procedure for Offloaded Mini-Apps Executed on Cluster Architectures with Xeon Phi Accelerators

Gary Lawson, Vaibhav Sundriyal, Masha Sosonkina, Yuzhong Shen

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, Molecular dynamics

September 9, 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

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

mt4g: Memory Topology 4 GPUs

MT4G: A Tool for Reliable Auto-Discovery of NVIDIA and AMD GPU Compute and Memory Topologies

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

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

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

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