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Real-Time Adaptive Image Compression

Oren Rippel, Lubomir Bourdev

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Tags: Algorithms, Compression, Computer science, Computer vision, Machine learning, nVidia, nVidia GeForce GTX 980 Ti

May 18, 2017 by hgpu

Block-Parallel IDA* for GPUs

Satoru Horie, Alex Fukunaga

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GRID K520, Package

May 11, 2017 by hgpu

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

Daniel J Magee, Kyle E Niemeyer

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Tags: Algorithms, cfd, Computational Physics, CUDA, Differential equations, Fluid dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Tesla K40

May 11, 2017 by hgpu

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Weihua Guo, You Xu, Xueyang Feng

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Tags: Biology, Computer science, Deep learning, Medicine, nVidia, nVidia GeForce GTX 1080, Package, Python, TensorFlow

May 11, 2017 by hgpu

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Konstantinos Krommydas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Package, Performance, Tesla K20, Thesis

May 9, 2017 by hgpu

Efficient Parallel Strategy Improvement for Parity Games

John Fearnley

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Logic in Computer Science, nVidia, nVidia GeForce GTX 780, Package

May 9, 2017 by hgpu

Acceleration of Deep Learning on FPGA

Huyuan Li

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Tags: CNN, Computer science, Deep learning, FPGA, Neural networks, nVidia, OpenCL, Tesla K40, Thesis

May 9, 2017 by hgpu

Multidimensional upwind hydrodynamics on unstructured meshes using Graphics Processing Units I. Two-dimensional uniform meshes

Sijme-Jan Paardekooper

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Tags: Algorithms, Astrophysics, cfd, Computational Physics, CUDA, Fluid dynamics, Instrumentation and Methods for Astrophysics, nVidia, Package, Tesla K20, Triangular meshes

May 9, 2017 by hgpu

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

Minsoo Rhu, Mike O'Connor, Niladrish Chatterjee, Jeff Pool, Stephen W. Keckler

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Tags: Compression, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, Virtualization

May 6, 2017 by hgpu

cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs

Antti-Pekka Hynninen, Dmitry I. Lyakh

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, nVidia, Package, Tesla K20, Tesla K40, Tesla M40, Tesla P100

May 6, 2017 by hgpu

Numerical Model of Shallow Water: the Use of NVIDIA CUDA Graphics Processors

Tatyana Dyakonova, Alexander Khoperskov, Sergey Khrapov

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Tags: cfd, Computer science, CUDA, Fluid dynamics, Numerical simulation, nVidia, Tesla C2070, Tesla K20, Tesla K40, Tesla K80

May 6, 2017 by hgpu

GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units

Zheyong Fan, Ville Vierimaa, Ari Harju

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Tags: Computational Physics, CUDA, nVidia, Package, Physics, Sparse matrix, Tesla K40

May 6, 2017 by hgpu

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

EnergyUCB-Bandit

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Real-Time Adaptive Image Compression

Block-Parallel IDA* for GPUs

Accelerating solutions of PDEs with GPU-based swept time-space decomposition

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Towards Enhancing Performance, Programmability, and Portability in Heterogeneous Computing

Efficient Parallel Strategy Improvement for Parity Games

Acceleration of Deep Learning on FPGA

Multidimensional upwind hydrodynamics on unstructured meshes using Graphics Processing Units I. Two-dimensional uniform meshes

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs

Numerical Model of Shallow Water: the Use of NVIDIA CUDA Graphics Processors

GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units

Recent source codes

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

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

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

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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