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Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Pietro Incardona, Aryaman Gupta, Serhii Yaskovets, Ivo F. Sbalzarini

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, OpenACC, OpenCL, OpenMP, Package, Performance, performance portability, SYCL

July 30, 2023 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

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Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

AvA: Accelerated Virtualization of Accelerators

Hangchen Yu, Arthur Michener Peters, Amogh Akshintala, Christopher J. Rossbach

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Tags: AMD Radeon RX 580, AMD RX Vega 64, ATI, Cloud, Code generation, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, Virtualization

March 1, 2020 by hgpu

Telekine: Secure Computing with Cloud GPUs

Tyler Hunt, Zhipeng Jia, Vance Miller, Ariel Szekely, Yige Hu, Christopher J. Rossbach, Emmett Witchel

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Tags: AMD RX Vega 64, ATI, Cloud, Computer science, nVidia, OpenCL, Security

March 1, 2020 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

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Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Automating Heterogeneous Parallelism in Numerical Differential Equations

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Transparent Acceleration of Java-based Deep Learning Engines

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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