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Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models

Jonathan A. Weyn, Dale R. Durran, Rich Caruana, Nathaniel Cresswell-Clay

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Tags: Deep learning, Earth and Space Sciences, Neural networks, nVidia, Tesla V100, Weather prediction, Weather Prediction Model

February 14, 2021 by hgpu

Transparent FPGA Acceleration with TensorFlow

Simon Pfenning, Philipp Holzinger, Marc Reichenbach

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Tags: Computer science, Deep learning, FPGA, Hardware Architecture, HSA, OpenCL, Package, TensorFlow

February 14, 2021 by hgpu

Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach

Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2070, Performance, Python, Tesla P100, Tesla V100

February 7, 2021 by hgpu

AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

Yuhan Liu, Saurabh Agarwal, Shivaram Venkataraman

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Tags: Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia A100, Package, Python, Tesla P100

February 7, 2021 by hgpu

Why is FPGA-GPU Heterogeneity the Best Option for Embedded Deep Neural Networks?

Walther Carballo-Hernández, Maxime Pelcat, François Berry

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, nVidia, nVidia Jetson TX2, Performance

February 7, 2021 by hgpu

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

Uttaran Bhattacharya, Nicholas Rewkowski, Abhishek Banerjee, Pooja Guhan, Aniket Bera, Dinesh Manocha

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Tags: Biomechanics, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Package, Virtual reality

January 31, 2021 by hgpu

Non-Parametric Adaptive Network Pruning

Lin Mingbao, Ji Rongrong, Li Shaojie, Wang Yan, Wu Yongjian, Huang Feiyue, Ye Qixiang

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Tags: Computer science, CUDA, Deep learning, nVidia, Package, PyTorch, Tesla V100

January 24, 2021 by hgpu

Implementation of Autoencoders with Systolic Arrays through OpenCL

Rafael Gadea-Gironés, Vicente Herrero-Bosch, Jose Monzó-Ferrer, Ricardo Colom-Paleros

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Tags: Algorithms, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL

January 17, 2021 by hgpu

Explainable Deep Behavioral Sequence Clustering for Transaction Fraud Detection

Wei Min, Weiming Liang, Hang Yin, Zhurong Wang, Mei Li, Alok Lal

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Tags: Algorithms, Clustering, Deep learning, Finance, nVidia, Risk Management, Tesla M40

January 17, 2021 by hgpu

Fast convolutional neural networks on FPGAs with hls4ml

Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Dylan Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang

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Tags: Benchmarking, Computer science, Deep learning, FPGA, Neural networks, Package

January 17, 2021 by hgpu

Advances in Electron Microscopy with Deep Learning

Jeffrey M. Ede

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Tags: Deep learning, Electron microscopy, Image processing, Machine learning, Microscopy, nVidia, nVidia GeForce GTX 1080 Ti, Package, Thesis

January 10, 2021 by hgpu

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, Yi-Hsuan Yang

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, Package

January 10, 2021 by hgpu

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

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

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

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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