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Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, S. Rajamanickam

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Tags: Computer science, CUDA, Differential equations, nVidia, OpenMP, Partial differential equations, PDEs, Tesla K20

November 24, 2015 by hgpu

Recurrent Neural Networks Hardware Implementation on FPGA

Andre Xian Ming Chang, Berin Martini, Eugenio Culurciello

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Tags: ARM, Computer science, FPGA, Machine learning, Neural networks, nVidia, nVidia Jetson TK1

November 20, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 2015 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Koki Nagano, Thomas Collins, Chi-An Chen, Aiichiro Nakano

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Tags: Algorithms, Computer science, GLSL, Particle swarm optimization, Rendering, Visualization

November 20, 2015 by hgpu

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

Garrick Orchard, Jacob G. Martin, R. Jacob Vogelstein, Ralph Etienne-Cummings

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Tags: Computer science, Computer vision, FPGA

November 13, 2015 by hgpu

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Anton Lokhmotov

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Tags: ARM, Benchmarking, Computer science, Linear Algebra, Mathematical Software, Matrix multiplication, OpenCL, Package, Performance

November 13, 2015 by hgpu

Accelerating Recommender Systems using GPUs

Andre Valente Rodrigues, Alipio Jorge, Ines Dutra

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 580

November 13, 2015 by hgpu

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

Gang Mei, Liangliang Xu, Nengxiong Xu

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Tags: Algorithms, Computer science, CUDA, Geoscience, nVidia, nVidia GeForce GT 730 M

November 13, 2015 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

Recurrent Neural Networks Hardware Implementation on FPGA

Supervised Hashing with Deep Neural Networks

Large Scale Artificial Neural Network Training Using Multi-GPUs

GPU-accelerated adjoint algorithmic differentiation

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Accelerating Recommender Systems using GPUs

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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