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BenchPress: A Deep Active Benchmark Generator

Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu, Chris Cummins, Kim Hazelwood, Ajitha Rajan, Hugh Leather

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Tags: Benchmarking, Code generation, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, PyTorch

August 21, 2022 by hgpu

Performance analysis of matrix-free conjugate gradient kernels using SYCL

Igor Baratta, Chris Richardson, Garth Wells

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Tags: Benchmarking, Computer science, Latency, nVidia, nVidia A100, OpenCL, Package, Performance, SYCL

August 21, 2022 by hgpu

Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training

Jie You, Jae-Won Chung, Mosharaf Chowdhury

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Tags: Computer science, Deep learning, Energy-efficient computing, Neural networks, nVidia, Package, Tesla V100

August 21, 2022 by hgpu

Optimization of GPU workloads using natural language processing based on deep learning techniques

Petros Vavaroutsos

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, OpenCL, Thesis

August 21, 2022 by hgpu

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, nVidia, nVidia A40, Package, PyTorch

August 21, 2022 by hgpu

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

Jose González-Abad, Álvaro López García, Valentin Y. Kozlov

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Tags: Computer science, CUDA, Deep learning, HPC, nVidia, nVidia GeForce GTX 980 Ti, Package, Tesla V100

August 7, 2022 by hgpu

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Francesco Barchi, Emanuele Parisi, Andrea Bartolini, Andrea Acquaviva

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Optimization, Overview, Security

August 7, 2022 by hgpu

Real-Time High-Performance Computing for Embedded Control Systems

Alejandro Josué Calderón Torres

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Tags: Code generation, Computer science, Embedded high-performance computing, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX2, OpenCL, Tesla T4, Tesla V100, Thesis

August 7, 2022 by hgpu

COX: Exposing CUDA Warp-Level Functions to CPUs

Ruobing Han, Jaewon Lee, Jaewoong Sim, Hyesoon Kim

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Tags: Benchmarking, Compilers, Computer science, CUDA, HIP, nVidia

August 7, 2022 by hgpu

Design and Implementation of ShenWei Universal C/C++

Huanqi Cao, Jiajie Chen

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

August 7, 2022 by hgpu

Demystifying Dependency Bugs in Deep Learning Stack

Kaifeng Huang, Bihuan Chen, Susheng Wu, Junmin Cao, Lei Ma, Xin Peng

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia

July 24, 2022 by hgpu

CPU-GPU Layer-Switched Low Latency CNN Inference

Ehsan Aghapour, Dolly Sapra, Andy Pimentel, and Anuj Pathania

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Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL, Package, SoC

July 24, 2022 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

BenchPress: A Deep Active Benchmark Generator

Performance analysis of matrix-free conjugate gradient kernels using SYCL

Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training

Optimization of GPU workloads using natural language processing based on deep learning techniques

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Real-Time High-Performance Computing for Embedded Control Systems

COX: Exposing CUDA Warp-Level Functions to CPUs

Design and Implementation of ShenWei Universal C/C++

Demystifying Dependency Bugs in Deep Learning Stack

CPU-GPU Layer-Switched Low Latency CNN Inference

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