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VitBit: Enhancing Embedded GPU Performance for AI Workloads through Register Operand Packing

Jaebeom Jeon, Minseong Gil, Junsu Kim, Jaeyong Park, Gunjae Koo, Myung Kuk Yoon, Yunho Oh

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Tags: AI, Artificial intelligence, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson AGX Orin, Performance

September 1, 2024 by hgpu

Anatomizing Deep Learning Inference in Web Browsers

Qipeng Wang, Shiqi Jiang, Zhenpeng Chen, Xu Cao, Yuanchun Li, Aoyu Li, Yun Ma, Ting Cao, Xuanzhe Liu

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1060, nVidia GeForce GTX 980, nVidia GeForce RTX 2060, OpenCL, Package, Performance, TensorFlow

August 18, 2024 by hgpu

A Comprehensive Deep Learning Library Benchmark and Optimal Library Selection

Qiyang Zhang, Xiangying Che, Yijie Chen, Xiao Ma, Mengwei Xu, Schahram Dustdar, Xuanzhe Liu, Shangguang Wang

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Tags: Benchmarking, Computer science, Deep learning, Heterogeneous systems, Package

August 14, 2024 by hgpu

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Junqing Lin, Jingwei Sun, Xiaolong Shi, Honghe Zhang, Xianzhi Yu, Xinzhi Wang, Jun Yao, Guangzhong Sun

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Tags: Compilers, Computer science, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Performance, Sparse matrix, Tesla V100

August 4, 2024 by hgpu

Data-driven Forecasting of Deep Learning Performance on GPUs

Seonho Lee, Amar Phanishayee, Divya Mahajan

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia H100, nVidia P100, nVidia V100, Performance, PyTorch, Tesla T4

August 4, 2024 by hgpu

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

Yizhou Luo, Qiang Wang, Shaohuai Shi, Jiaxin Lai, Shuhan Qi, Jiajia Zhang, Xuan Wang

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Tags: Computer science, CUDA, Deep learning, GPU cluster, nVidia, nVidia GeForce RTX 2080 Ti, OpenMPI, PyTorch, Task scheduling

August 4, 2024 by hgpu

Data-driven Performance Optimization for Data-intensive Applications

Jie Liu

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Tags: Computer science, Databases, Deep learning, Neural networks, nVidia, nVidia V100, TensorFlow, Thesis

July 28, 2024 by hgpu

An End-to-End Programming Model for AI Engine Architectures

Maksim Levental

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3080 Ti, Thesis, Vulkan

June 23, 2024 by hgpu

How much can we gain from Tensor Kernel Fusion on GPUs?

Wei Sun, Ang Li, Sander Stuijk, Henk Corporaal

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Tags: Computer science, CUDA, Deep learning, Matrix multiplication, Neural networks, nVidia, nVidia A100, nVidia H100

June 16, 2024 by hgpu

A Survey of Cloud-Based GPU Threats and Their Impact on AI, HPC, and Cloud Computing

Numaan Huq, Philippe Lin, Roel Reyes, Charles Perine

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Tags: AMD Radeon Pro V520, Artificial intelligence, ATI, Cloud, Computer science, CUDA, Deep learning, nVidia, OpenCL, Security, Tesla T4

June 2, 2024 by hgpu

ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution

Guillaume Couairon, Christian Lessig, Anastase Charantonis, Claire Monteleoni

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Tags: Deep learning, Earth and Space Sciences, nVidia, nVidia A100, Weather prediction

May 26, 2024 by hgpu

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Roberto L. Castro, Diego Andrade, Basilio B. Fraguela

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Tags: Auto-Tuning, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia A100, Tesla T4

May 26, 2024 by hgpu

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

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

VitBit: Enhancing Embedded GPU Performance for AI Workloads through Register Operand Packing

Anatomizing Deep Learning Inference in Web Browsers

A Comprehensive Deep Learning Library Benchmark and Optimal Library Selection

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Data-driven Forecasting of Deep Learning Performance on GPUs

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

Data-driven Performance Optimization for Data-intensive Applications

An End-to-End Programming Model for AI Engine Architectures

How much can we gain from Tensor Kernel Fusion on GPUs?

ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Recent source codes

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

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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