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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

Parallel waveform extraction algorithms for the Cherenkov Telescope Array Real-Time Analysis

Andrea Zoli, Andrea Bulgarelli, Adriano De Rosa, Alessio Aboudan, Valentina Fioretti, Giovanni De Cesare, Ramin Marx

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Tags: Astrophysics, FPGA, nVidia, OpenCL, OpenMP, Tesla K40

September 9, 2015 by hgpu

A Performance Comparison of Algebraic Multigrid Preconditioners on CPUs, GPUs, and Xeon Phis

K. Rupp, J. Weinbub, F. Rudolf, A. Morhammer, T. Grasser, A. Jungel

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Tags: AMD FirePro W9100, ATI, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, OpenMP, Performance, Tesla K20

September 9, 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

Dissecting GPU Memory Hierarchy through Microbenchmarking

Xinxin Mei, Xiaowen Chu

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Tags: Benchmarking, cache, Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, nVidia GeForce GTX 980, Package

September 9, 2015 by hgpu

Accelerating Multiple Compound Comparison Using LINGO-based Load-Balancing Strategies on Multi-GPUs

Chun-Yuan Lin, Chung-Hung Wang, Che-Lun Hung, Yu-Shiang Lin

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Tags: Computer science, CUDA, load balancing, nVidia, OpenMP, Tesla K20

September 8, 2015 by hgpu

Assessing the hardness of SVP algorithms in the presence of CPUs and GPUs

Fabio Jose Goncalves Correia

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, Quantum computing, Security, Thesis, Voronoi diagram

September 8, 2015 by hgpu

Contributions to the Efficient Use of General Purpose Coprocessors: Kernel Density Estimation as Case Study

Unai Lopez Novoa

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Tags: Algorithms, ATI, ATI Radeon HD 6950, Computational Complexity, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 650, OpenCL, Thesis

September 8, 2015 by hgpu

Accelerating Web Search using GPUs

Rimon Tadros

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Tags: C++ AMP, Computer science, nVidia, nVidia GeForce GTX 660 Ti, nVidia GeForce GTX 750 Ti, Search, Thesis

September 8, 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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