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A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 by hgpu

Analysis of A Splitting Approach for the Parallel Solution of Linear Systems on GPU Cards

Ang Li, Radu Serban, Dan Negrut

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Package, Sparse direct solvers, Tesla K20

September 30, 2015 by hgpu

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

John-Alexander M. Assael

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Tags: CNN, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Tesla K40, Thesis

September 26, 2015 by hgpu

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Gunther Lukat, Robi Banerjee

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Tags: Astrophysics, CUDA, Fortran, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla C2075

September 26, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

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Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 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

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

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

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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