high performance computing on graphics processing units: hgpu.org

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MALBEC: a new CUDA-C ray-tracer in General Relativity

G. D. Quiroga

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Tags: CUDA, General Relativity and Quantum Cosmology, nVidia, nVidia GeForce GTX 960 M, Package, Physics

March 25, 2018 by hgpu

Accelerating CNN inference on FPGAs: A Survey

Kamel Abdelouahab, Maxime Pelcat, Jocelyn Serot, Francois Berry

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

March 25, 2018 by hgpu

The VOLNA-OP2 Tsunami Code (Version 1.0)

Istvan Z Reguly, Devaraj Gopinathan, Joakim H Beck, Michael B Giles, Serge Guillas, Frederic Dias

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Tags: CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, Package, Tesla P100

March 22, 2018 by hgpu

FPGA in HPC: High Level Synthesys of OpenCL kernels for Molecular Dynamics

Paolo Gorlani

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Tags: Computer science, FPGA, Molecular dynamics, OpenCL, Thesis

March 22, 2018 by hgpu

A multi-agent architecture for scheduling of high performance services in a GPU cluster

Joel Antonio Trejo-Sanchez, Jose Luis Lopez-Martinez, Jose Octavio Gutierrez Garcia, Julio Cesar Ramirez-Pacheco, Daniel Fajardo-Delgado

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Tags: Computer science, GPU cluster, Heterogeneous systems

March 22, 2018 by hgpu

TBD: Benchmarking and Analyzing Deep Neural Network Training

Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan XP, nVidia Quadro P 4000

March 22, 2018 by hgpu

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Kazuaki Matsumura, Mitsuhisa Sato, Taisuke Boku, Artur Podobas, Satoshi Matsuoka

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Tags: Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla P100

March 22, 2018 by hgpu

HPVM: Heterogeneous Parallel Virtual Machine

Maria Kotsifakou, Prakalp Srivastava, Matthew D. Sinclair, Rakesh Komuravelli, Vikram Adve, Sarita Adve

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

March 17, 2018 by hgpu

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis

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Tags: Artificial intelligence, Computer science, Deep learning, Design space exploration, FPGA, OpenCL, survey

March 17, 2018 by hgpu

CuLDA_CGS: Solving Large-scale LDA Problems on GPUs

Xiaolong Xie, Yun Liang, Xiuhong Li, Wei Tan

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Tags: Algorithms, Computer science, CUDA, Latent Dirichlet allocation, Machine learning, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce GTX Titan XP, Package, Tesla V100

March 17, 2018 by hgpu

Improved OpenCL-based Implementation of Social Field Pedestrian Model

Bin Yu, Ke Zhu, Kaiteng Wu, Michael Zhang

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Tags: Algorithms, Computer science, OpenCL

March 17, 2018 by hgpu

NVIDIA Tensor Core Programmability, Performance & Precision

Stefano Markidis, Steven Wei Der Chien, Erwin Laure, Ivy Bo Peng, Jeffrey S. Vetter

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Tags: Computer science, CUDA, Mixed precision, nVidia, Performance, Tesla V100

March 17, 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

MALBEC: a new CUDA-C ray-tracer in General Relativity

Accelerating CNN inference on FPGAs: A Survey

The VOLNA-OP2 Tsunami Code (Version 1.0)

FPGA in HPC: High Level Synthesys of OpenCL kernels for Molecular Dynamics

A multi-agent architecture for scheduling of high performance services in a GPU cluster

TBD: Benchmarking and Analyzing Deep Neural Network Training

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

HPVM: Heterogeneous Parallel Virtual Machine

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

CuLDA_CGS: Solving Large-scale LDA Problems on GPUs

Improved OpenCL-based Implementation of Social Field Pedestrian Model

NVIDIA Tensor Core Programmability, Performance & Precision

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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