high performance computing on graphics processing units: hgpu.org

René Caspart, Sebastian Ziegler, Arvid Weyrauch, Holger Obermaier, Simon Raffeiner, Leon Pascal Schuhmacher, Jan Scholtyssek, Darya Trofimova, Marco Nolden, Ines Reinartz, Fabian Isensee, Markus Götz, Charlotte Debus

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Tags: Artificial intelligence, Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, Package

December 11, 2022 by hgpu

Mixing Low-Precision Formats in Multiply-Accumulate Units for DNN Training

Mariko Tatsumi, Silviu-Ioan Filip, Caroline White, Olivier Sentieys, Guy Lemieux

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Tags: Computer science, CUDA, Deep learning, FPGA, nVidia, Precision

December 11, 2022 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

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

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Applications

Extending MAGMA Portability with OneAPI

mu-grind: A Framework for Dynamically Instrumenting HLS-Generated RTL

GPU Load Balancing

A Framework to Generate High-Performance Time-stepped Agent-based Simulations on Heterogeneous Hardware

Code Generation from Functional to Imperative: Combining Destination-Passing Style and Views

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

A Study on the Intersection of GPU Utilization and CNN Inference

FLIA: Architecture of Collaborated Mobile GPU and FPGA Heterogeneous Computing

Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads

Mixing Low-Precision Formats in Multiply-Accumulate Units for DNN Training

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA