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Dr.Jit: A Just-In-Time Compiler for Differentiable Rendering

Wenzel Jakob, Sébastien Speierer, Nicolas Roussel, Delio Vicini

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Tags: 3D Graphics and Realism, Algorithms, Code generation, CUDA, nVidia, nVidia RTX A6000, Python, Rendering

February 6, 2022 by hgpu

SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets

Xiaodong Yu, Sheng Di, Kai Zhao, jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia A100, Tesla V100

February 6, 2022 by hgpu

GC3: An Optimizing Compiler for GPU Collective Communication

Meghan Cowan, Saeed Maleki, Madanlal Musuvathi, Olli Saarikivi, Yifan Xiong

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Tags: Algorithms, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia A100

February 6, 2022 by hgpu

Teaching Parallel Programming in Containers: Virtualization of a Heterogeneous Local Infrastructure

Naylor Garcia Bachiega

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, nVidia, nVidia GeForce GTX 650, Package, Thesis, Virtualization

January 30, 2022 by hgpu

Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs

Cody Rivera, Sheng Di, Jiannan Tian, Xiaodong Yu, Dingwen Tao, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, Package, Tesla V100

January 30, 2022 by hgpu

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

Jou-An Chen, Hsin-Hsuan Sung, Nathan Tallent, Kevin Barker, Xipeng Shen, Ang Li

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan V, Package, Sparse

January 30, 2022 by hgpu

Multi-hetero Acceleration by GPU and FPGA for Astrophysics Simulation on oneAPI Environment

Ryuta Kashino, Ryohei Kobayashi, Norihisa Fujita, Taisuke Boku

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Tags: Astrophysics, CUDA, FPGA, Heterogeneous systems, nVidia, OpenCL, Physics, SYCL

January 23, 2022 by hgpu

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics

Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis

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Tags: Biology, Chemistry, CUDA, GeForce RTX 2080 Ti, Machine learning, Molecular dynamics, Molecular simulation, Neural networks, nVidia, Package

January 23, 2022 by hgpu

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan XP, Package, Performance, Tesla P100, Tesla V100

January 23, 2022 by hgpu

Research and Development of Porting SYCL on QNX Operating System for High Parallelism

Dengpan Wang

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Operating systems, PTX, SYCL, Thesis

January 16, 2022 by hgpu

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Mhd Ghaith Olabi, Juan Gómez Luna, Onur Mutlu, Wen-mei Hwu, Izzat El Hajj

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Tags: Compilers, Computer science, CUDA, nVidia, Package, Performance, Tesla V100

January 16, 2022 by hgpu

Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment

Hulin Dai, Xuan Peng, Xuanhua Shi, Ligang He, Qian Xiong, Hai Jin

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Neural networks, nVidia, Performance, PyTorch, TensorFlow, Tesla P100

January 9, 2022 by hgpu

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

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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high performance computing on graphics processing units: hgpu.org

Dr.Jit: A Just-In-Time Compiler for Differentiable Rendering

SZx: an Ultra-fast Error-bounded Lossy Compressor for Scientific Datasets

GC3: An Optimizing Compiler for GPU Collective Communication

Teaching Parallel Programming in Containers: Virtualization of a Heterogeneous Local Infrastructure

Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

Multi-hetero Acceleration by GPU and FPGA for Astrophysics Simulation on oneAPI Environment

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Research and Development of Porting SYCL on QNX Operating System for High Parallelism

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

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

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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