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TinyDL: Just-In-Time Deep Learning Solution For Constrained Embedded Systems

Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar

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Tags: ARM, Computer science, CUDA, Deep learning, nVidia, nVidia Jetson TK1, Performance

May 2, 2017 by hgpu

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Michail Alvanos, Theodoros Christoudias

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Tags: Chemistry, Code generation, CUDA, Earth and Space Sciences, Fortran, nVidia, Package, Tesla M2070

May 2, 2017 by hgpu

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

J.E. Adsuara, I. Cordero-Carrion, P. Cerda-Duran, M.A. Aloy

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Tags: CUDA, Differential equations, Finite difference, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs, Tesla K40

May 2, 2017 by hgpu

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Bin Chen, Ronald Kantowski, Xinyu Dai, Eddie Baron, Paul Van der Mark

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Tags: Astrophysics, CUDA, Gravitation, Gravitational lensing, Intel Xeon Phi, nVidia, OpenMP, Tesla M2050

May 2, 2017 by hgpu

Deep Learning in the Automotive Industry: Applications and Tools

Andre Luckow, Matthew Cook, Nathan Ashcraft, Edwin Weill, Emil Djerekarov, Bennie Vorster

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Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia GRID K520, Performance

May 2, 2017 by hgpu

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X

April 30, 2017 by hgpu

Automatic source code adaptation for heterogeneous platforms

Albert Saa-Garriga

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Tesla M2050, Thesis

April 30, 2017 by hgpu

Accelerating Discrete Wavelet Transforms on Parallel Architectures

David Barina, Michal Kula, Michal Matysek, Pavel Zemcik

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Discrete Wavelet Transform, Image processing, nVidia, nVidia GeForce GTX Titan X, OpenCL, OpenGL, Performance, Pixel shaders

April 30, 2017 by hgpu

Low-complexity Distributed Tomographic Backprojection for large datasets

Gilberto Martinez Jr., Janito V. Ferreira Filho, Eduardo X. Miqueles

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, nVidia GeForce GTX X, nVidia Tegra TX1, Package, Tomography

April 30, 2017 by hgpu

Developing a massive real-time crowd simulation framework on the GPU

Guillaume Payet

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Tags: Algorithms, Computer science, Crowd simulation, nVidia, nVidia GeForce GTX 850 M, OpenCL, Thesis

April 26, 2017 by hgpu

A Training Framework and Architectural Design for Distributed Deep Learning

Wei Wang

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan X, Package, Python, Thesis

April 26, 2017 by hgpu

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

Suejb Memeti, Lu Li, Sabri Pllana, Joanna Kolodziej, Christoph Kessler

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Performance

April 20, 2017 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

TinyDL: Just-In-Time Deep Learning Solution For Constrained Embedded Systems

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Automatic source code adaptation for heterogeneous platforms

Accelerating Discrete Wavelet Transforms on Parallel Architectures

Low-complexity Distributed Tomographic Backprojection for large datasets

Developing a massive real-time crowd simulation framework on the GPU

A Training Framework and Architectural Design for Distributed Deep Learning

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

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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