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Characterising Bipartite Graph Matching Algorithms on GPUs

Stanley Tsang

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla K20, Thesis

February 23, 2015 by hgpu

Investigation of the OpenCL SYCL Programming Model

Angelos Trigkas

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Thesis

February 23, 2015 by hgpu

Asynchronous OpenCL/MPI numerical simulations of conservation laws

Philippe Helluy, Thomas Strub, Michel Massaro, Malcolm Roberts

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Tags: ATI, ATI Radeon HD 7970, MPI, Numerical simulation, nVidia, OpenCL, Physics, Tesla K20

February 23, 2015 by hgpu

Stochastic Gradient Descent on GPUs

Rashid Kaleem, Sreepathi Pai, Keshav Pingali

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Tags: Algorithms, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla K40

February 22, 2015 by hgpu

High performance methods for frequent pattern mining

Lan Vu

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, Tesla C2050, Thesis

February 22, 2015 by hgpu

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut

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Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenCL, Performance, Python, Sparse matrix, Tesla K20

February 22, 2015 by hgpu

QPACE 2 and Domain Decomposition on the Intel Xeon Phi

Paul Arts, Jacques Bloch, Peter Georg, Benjamin Glaessle, Simon Heybrock, Yu Komatsubara, Robert Lohmayer, Simon Mages, Bernhard Mendl, Nils Meyer, Alessio Parcianello, Dirk Pleiter, Florian Rappl, Mauro Rossi, Stefan Solbrig, Giampietro Tecchiolli, Tilo Wettig, Gianpaolo Zanier

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Tags: Benchmarking, Computational Physics, Computer science, High Energy Physics - Lattice, Intel Xeon Phi

February 22, 2015 by hgpu

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Sergey Voronin, Per-Gunnar Martinsson

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Tags: Algorithms, CUDA, CULA, Mathematical Software, Mathematics, Matrix decomposition, Numerical Analysis, nVidia, Package, Tesla M2070

February 22, 2015 by hgpu

Exploring Design Space of 3D NVM and eDRAM Caches Using DESTINY Tool (open-source code)

Sparsh Mittal, Matt Poremba, Jeffrey Vetter, Yuan Xie

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Tags: Architecture, area, cache, cpu, energy, GPGPU, latency modeling, Memory, Package

February 22, 2015 by sparsh0mittal

Reproducible Triangular Solvers for High-Performance Computing

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

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Tags: Algorithms, Computer science, Linear Algebra, nVidia, nVidia Quadro K5000, OpenCL, Package, Tesla K20

February 19, 2015 by hgpu

Fast, Memory-Efficient Construction of Voxelized Shadows

Viktor Kampe, Erik Sintorn, Ulf Assarsson

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, OpenGL, Real-time graphics, Rendering

February 19, 2015 by hgpu

Auto-tuning Shallow water simulations on GPUs

Andre B. Amundsen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia Quadro 1800 M, Rendering, Thesis

February 19, 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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