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Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numerical Behaviors

Wei Sun, Ang Li, Tong Geng, Sander Stuijk, Henk Corporaal

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Tags: Benchmarking, Computer science, Matrix multiplication, nVidia, nVidia A100, nVidia GeForce RTX 2080, nVidia GeForce RTX 2080 Ti, Performance, PTX, Sparse matrix

June 12, 2022 by hgpu

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Andy Adinets, Duane Merrill

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia A100, Package, Performance, Sorting

June 12, 2022 by hgpu

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

John Keith Holmen

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX Titan X, performance portability, Task scheduling

June 5, 2022 by hgpu

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

Ali Mokhtari, Pooyan Jamshidi, Mohsen Amini Salehi

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Tags: Computer science, FPGA, Heterogeneous systems, Machine learning, nVidia, Package, Tesla M60

June 5, 2022 by hgpu

Walle: An End-to-End, General-Purpose, and Large-Scale Production System for Device-Cloud Collaborative Machine Learning

Chengfei Lv, Chaoyue Niu, Renjie Gu, Xiaotang Jiang, Zhaode Wang, Bin Liu, Ziqi Wu, Qiulin Yao, Congyu Huang, Panos Huang, Tao Huang, Hui Shu, Jinde Song, Bin Zou, Peng Lan, Guohuan Xu, Fei Wu, Shaojie Tang, Fan Wu, Guihai Chen

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Tags: Cloud, Computer science, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Python

June 5, 2022 by hgpu

End-to-end Optimization of Machine Learning Prediction Queries

Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos

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Tags: Computer science, Databases, Machine learning, nVidia, Tesla K80, Tesla P100

June 5, 2022 by hgpu

User’s needs influencing HPC technologies

E. Athanasaki, N. Meyer, M. Cestari, A.Tuncer Durak, A. Tekin, P. Gschwandtner

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Tags: AI, Artificial intelligence, Cloud, Computer science, CUDA, HIP, HPC, nVidia, OpenCL, Security, SYCL

May 29, 2022 by hgpu

Fast GPU bounding boxes on tree-structured scenes

Raph Levien

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Tags: 3D Graphics and Realism, AMD Radeon RX 5700 XT, ATI, GLSL, HLSL, nVidia, nVidia GeForce GTX 1080, Package, Rendering, Vulkan

May 29, 2022 by hgpu

SOL: Reducing the Maintenance Overhead for Integrating Hardware Support into AI Frameworks

Nicolas Weber

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Tags: AI, Artificial intelligence, Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, Performance

May 29, 2022 by hgpu

Fault Injection techniques for GPU Reliability Evaluation

Luigi Galasso

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Tags: Computer science, CUDA, Fault simulation, nVidia, Thesis

May 29, 2022 by hgpu

Lossless Acceleration for Seq2seq Generation with Aggressive Decoding

Tao Ge, Heming Xia, Xin Sun, Si-Qing Chen, Furu Wei

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, Package, Tesla V100

May 29, 2022 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

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

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Applications

Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numerical Behaviors

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

End-to-end Optimization of Machine Learning Prediction Queries

Fast GPU bounding boxes on tree-structured scenes

SOL: Reducing the Maintenance Overhead for Integrating Hardware Support into AI Frameworks

Fault Injection techniques for GPU Reliability Evaluation

Lossless Acceleration for Seq2seq Generation with Aggressive Decoding

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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