high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Balancing locality and concurrency: solving sparse triangular systems on GPUs

Andrea Picciau, Gordon E. Inggs, John Wickerson, Eric C. Kerrigan, George A. Constantinides

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Tags: Algorithms, AMD FirePro W5000, ATI, Computer science, Linear Algebra, nVidia, nVidia Quadro K4000, OpenCL, Sparse matrix

November 8, 2016 by hgpu

Tamp: A Library for Compact Deep Neural Networks with Structured Matrices

Bingchen Gong, Brendan Jou, Felix Yu, Shih-Fu Chang

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Tags: Caffe, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, TensorFlow

November 8, 2016 by hgpu

Accelerate Deep Learning Inference with MCTS in the game of Go on the Intel Xeon Phi

Ching-Nung Lin, Shi-Jim Yen

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Tags: Computer science, Deep learning, Intel Xeon Phi, Neural networks

November 8, 2016 by hgpu

Performance Portability of the Aeras Atmosphere Model to Next Generation Architectures using Kokkos

Jerry Watkins, Irina Tezaur

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Tags: CUDA, Earth and Space Sciences, MPI, nVidia, OpenMP, performance portability, Physics, Tesla K20, Tesla K80

November 8, 2016 by hgpu

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

Woohyuk Choi, Sumin Hong, Won-Ki Jeong

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Tags: Clustering, Computer science, CUDA, Distributed computing, DSL, GPU cluster, Image processing, MapReduce, nVidia, nVidia GeForce GTX Titan, Python, Rendering, Spark

November 8, 2016 by hgpu

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Tarun Beri

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Tags: Computer science, CUDA, FFT, GPU cluster, Linear Algebra, Matrix multiplication, nVidia, Package, Prefetch, Tesla M2070, Thesis

November 5, 2016 by hgpu

HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems

Prakalp Srivastava, Maria Kotsifakou, Vikram Adve

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Tags: Code generation, Computer science, Data parallelism, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, performance portability

November 5, 2016 by hgpu

Molecular Activity Prediction using Deep Learning Software Library

Yoshiki Kato, Shinji Hamada, Hitoshi Goto

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Tags: Bioinformatics, Chemistry, Computer science, CUDA, Deep learning, nVidia, Package, Python, Tesla K20

November 5, 2016 by hgpu

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

Elias Stehle, Hans-Arno Jacobsen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, Sorting

November 5, 2016 by hgpu

grim: A Flexible, Conservative Scheme for Relativistic Fluid Theories

Mani Chandra, Francois Foucart, Charles F. Gammie

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Tags: Astrophysics, Magnetohydrodynamics, nVidia, OpenCL, Package, Physics, Tesla K20

November 5, 2016 by hgpu

Diplomat: Mapping of multi-kernel applications using a static dataflow abstraction

Bruno Bodin, Luigi Nardi, Paul H. J. Kelly, Michael F. P. O'Boyle

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Tags: ARM, Computer science, Computer vision, Heterogeneous systems, OpenCL

November 3, 2016 by hgpu

Extensions and Limitations of the Neural GPU

Eric Price, Wojciech Zaremba, Ilya Sutskever

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, Package, Python

November 3, 2016 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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high performance computing on graphics processing units: hgpu.org

Applications

Balancing locality and concurrency: solving sparse triangular systems on GPUs

Tamp: A Library for Compact Deep Neural Networks with Structured Matrices

Accelerate Deep Learning Inference with MCTS in the game of Go on the Intel Xeon Phi

Performance Portability of the Aeras Atmosphere Model to Next Generation Architectures using Kokkos

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems

Molecular Activity Prediction using Deep Learning Software Library

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

grim: A Flexible, Conservative Scheme for Relativistic Fluid Theories

Diplomat: Mapping of multi-kernel applications using a static dataflow abstraction

Extensions and Limitations of the Neural GPU

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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