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Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Keunwoo Choi, Deokjin Joo, Juho Kim

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Tags: Computer science, CUDA, Deep learning, Keras, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X, Package, Python, Signal processing, Tesla K80, Tesla M60

June 21, 2017 by hgpu

Efficient OpenCL-based concurrent tasks offloading on accelerators

A.J. Lazaro-Munoz, J.M. Gonzalez-Linares, J. Gomez-Luna, N. Guil

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Tags: AMD Radeon R9, ATI, Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Task scheduling, Tesla K20

June 17, 2017 by hgpu

Device Placement Optimization with Reinforcement Learning

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Neural networks, nVidia, TensorFlow, Tesla K80

June 17, 2017 by hgpu

Crane – Fast and Migratable GPU Passthrough for OpenCL applications

James Gleeson, Daniel Kats, Charlie Mei, Eyal de Lara

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Tags: Computer science, nVidia, nVidia Grid K1, OpenCL, Virtualization

June 10, 2017 by hgpu

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Priya Goyal, Piotr Dollar, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, Kaiming He

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla P100

June 10, 2017 by hgpu

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian

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

June 10, 2017 by hgpu

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Vladimir Lekic, Zdenka Babic

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Tags: ATI, ATI Radeon HD 5770, Computer science, Deep learning, Heterogeneous systems, Neural networks, OpenCL

June 5, 2017 by hgpu

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Mohammed A. Noaman Al-hayanni, Rishad Shafik, Ashur Rafiev, Fei Xia, Alex Yakovlev

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

June 5, 2017 by hgpu

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

Herman Noel Hoffman

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

Vincent Mirian

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, SoC, Thesis

June 5, 2017 by hgpu

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Mark W. Lewis

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Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTS 780 Ti

June 5, 2017 by hgpu

A performance spectrum for parallel computational frameworks that solve PDEs

J. Chang, K. B. Nakshatrala, M. G. Knepley, L. Johnsson

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Tags: Computational Physics, Computer science, Intel Xeon Phi, Mathematical Software, MPI, Partial differential equations, PDEs

June 1, 2017 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Applications

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

Efficient OpenCL-based concurrent tasks offloading on accelerators

Device Placement Optimization with Reinforcement Learning

Crane – Fast and Migratable GPU Passthrough for OpenCL applications

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

Neneta: Heterogeneous Computing Complex-Valued Neural Network Framework

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Program Acceleration in a Heterogeneous Computing Environment Using OpenCL, FPGA, and CPU

UT-OCL: An OpenCL Framework for Embedded Systems Using Xilinx FPGAs

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

A performance spectrum for parallel computational frameworks that solve PDEs

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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