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hgpu.org » Applications » Computer science

Towards Predictable Real-Time Performance on Multi-Core Platforms

Hyoseung Kim

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Tags: Computer science, Performance, Sensing, Thesis, Virtualization

July 30, 2016 by hgpu

Particle-in-cell algorithms for plasma simulations on heterogeneous architectures

Xavier Saez Pous

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Tags: ARM, Computational Physics, Computer science, Heterogeneous systems, MPI, OpenCL, Particle-in-cell methods, Plasma physics, Thesis

July 30, 2016 by hgpu

An Autotuning Framework for Intel Xeon Phi Platforms

Lefteris Christoforidis

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Tags: Computer science, Intel Xeon Phi, Package, Performance, Python, Thesis

July 30, 2016 by hgpu

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures

Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter Sadowski, Evan Racah, Suren Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey

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Tags: Algorithms, classification, Computer science, Data mining, Intel Xeon Phi, KD-tree, Machine learning, Nearest neighbour

July 30, 2016 by hgpu

Many-Core Algorithms for Combinatorial Optimization

Francesco Strappaveccia

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 570, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenMP, Optimization, Path problems, Thesis

July 28, 2016 by hgpu

Genetic Improvement of GPU Software

William B. Langdon, Brian Yee Hong Lam, Marc Modat, Justyna Petke, Mark Harman

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Tesla C2050, Tesla K20, Tesla T10

July 28, 2016 by hgpu

Real-Time Stochastic Kinodynamic Motion Planning via Multiobjective Search on GPUs

Brian Ichter, Edward Schmerling, Ali-akbar Agha-mohammadi, Marco Pavone

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980, Package, Robotics

July 28, 2016 by hgpu

FPGA-Based Accelerator Design from a Domain-Specific Language

M. Akif Ozkan, Oliver Reiche, Frank Hannig, Jurgen Teich

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Tags: Algorithms, Computer vision, FPGA, Heterogeneous systems, Image processing, nVidia, nVidia Jetson TK1, OpenCL, Tesla K20

July 26, 2016 by hgpu

Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

Marius Erbert, Steffen Rechner, Matthias Muller-Hannemann

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, Package

July 26, 2016 by hgpu

GPU-accelleration of image rendering and sorting algorithms with the OpenCL framework

Anders Soderholm, Justus Sorman

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Tags: Algorithms, Computer science, Heterogeneous systems, Image processing, Intel HD 4600, OpenCL, Rendering, Sorting, Thesis

July 26, 2016 by hgpu

Algorithmic Trading: A brief, computational finance case study on data centre FPGAs

Gordon Inggs

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, nVidia, nVidia Quadro K4000, OpenCL

July 20, 2016 by hgpu

Lowering IrGL to CUDA

Sreepathi Pai, Keshav Pingali

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Tags: Compilers, Computer science, CUDA, nVidia, Programming Languages

July 20, 2016 by hgpu

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Towards Predictable Real-Time Performance on Multi-Core Platforms

Particle-in-cell algorithms for plasma simulations on heterogeneous architectures

An Autotuning Framework for Intel Xeon Phi Platforms

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures

Many-Core Algorithms for Combinatorial Optimization

Genetic Improvement of GPU Software

Real-Time Stochastic Kinodynamic Motion Planning via Multiobjective Search on GPUs

FPGA-Based Accelerator Design from a Domain-Specific Language

Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

GPU-accelleration of image rendering and sorting algorithms with the OpenCL framework

Algorithmic Trading: A brief, computational finance case study on data centre FPGAs

Lowering IrGL to CUDA

Recent source codes

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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