high performance computing on graphics processing units: hgpu.org

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Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Jialiang Zhang, Soroosh Khoram, Jing Li

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Tags: Computer science, FPGA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan XP, OpenCL

June 13, 2018 by hgpu

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang

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Tags: Computer science, Intel Xeon Phi, Machine learning, OpenMP, Performance, Sparse matrix

June 9, 2018 by hgpu

GPU Virtualization and Scheduling Methods: A Comprehensive Survey

Cheol-Ho Hong, Ivor Spence, Dimitrios S. Nikolopoulos

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Tags: Cloud, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Review, Virtualization

June 9, 2018 by hgpu

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Y. Huang, J. Shen, Z. Wang, M. Wen, C. Zhang

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Tags: Computational Complexity, Computer science, Computer vision, Deep learning, FPGA, HLS, Neural networks

June 9, 2018 by hgpu

Fast Locality Sensitive Hashing for Beam Search on GPU

Xing Shi, Shizhen Xu, Kevin Knight

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Data Structures and Algorithms, Hashing, NLP, nVidia, Tesla K20

June 9, 2018 by hgpu

Deep Fluids: A Generative Network for Parameterized Fluid Simulations

Byungsoo Kim, Vinicius C. Azevedo, Nils Thuerey, Theodore Kim, Markus Gross, Barbara Solenthaler

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Tags: cfd, Deep learning, Fluid dynamics, Fluid simulation, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X, TensorFlow

June 9, 2018 by hgpu

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

Jing Chen, Jianbin Fanga, Weifeng Liub, Tao Tang, Canqun Yang

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Tags: AMD Radeon R9 Fury X, ATI, Computer science, Factorization, Linear Algebra, nVidia, OpenCL, Package, Tesla K20

June 2, 2018 by hgpu

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

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Tags: Algorithms, CNN, Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, OpenCL

June 2, 2018 by hgpu

NengoDL: Combining deep learning and neuromorphic modelling methods

Daniel Rasmussen

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Tags: Artificial intelligence, Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Python

June 2, 2018 by hgpu

Marian: Cost-effective High-Quality Neural Machine Translation in C++

Marcin Junczys-Dowmunt, Kenneth Heafield, Hieu Hoang, Roman Grundkiewicz, Anthony Aue

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, Package

June 2, 2018 by hgpu

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

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Tags: AMD Radeon R7 370, Astrophysics, ATI, FPGA, OpenCL

June 2, 2018 by hgpu

OpenCL 2.2 API Specification

Khronos OpenCL Working Group

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Tags: Computer science, OpenCL, Whitepaper

May 26, 2018 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Applications

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Fast Locality Sensitive Hashing for Beam Search on GPU

Deep Fluids: A Generative Network for Parameterized Fluid Simulations

clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

NengoDL: Combining deep learning and neuromorphic modelling methods

Marian: Cost-effective High-Quality Neural Machine Translation in C++

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

OpenCL 2.2 API Specification

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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