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Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance

Jiarong Xing, Leyuan Wang, Shang Zhang, Jack Chen, Ang Chen, Yibo Zhu

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Tags: Auto-Tuning, Computer science, CUDA, Deep learning, Neural networks, nVidia, Performance, Tesla T4

October 31, 2021 by hgpu

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry

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Tags: Compilers, Computer science, CUDA, Deep learning, nVidia, Tesla V100

October 24, 2021 by hgpu

Monitoring Collective Communication Among GPUs

Muhammet Abdullah Soyturk, Palwisha Akhtar, Erhan Tezcan, Didem Unat

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Tags: Computer science, CUDA, MPI, nVidia, Package, Performance, Tesla V100

October 24, 2021 by hgpu

Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads

Cesar A. Baddouh, Mahmoud Khairy, Roland Green, Mathias Payer, Timothy G. Rogers

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Tags: Computer science, CUDA, nVidia, Performance, Tesla V100

October 24, 2021 by hgpu

OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems

Nawras Alnaasan, Arpan Jain, Aamir Shafi, Hari Subramoni, Dhabaleswar K Panda

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Tags: Benchmarking, Computer science, CUDA, Deep learning, HPC, Machine learning, MPI, nVidia, Python, Tesla V100

October 24, 2021 by hgpu

Least Squares on GPUs in Multiple Double Precision

Jan Verschelde

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Tags: Code generation, Computer science, CUDA, Mathematical Software, nVidia, Package, Tesla P100, Tesla V100

October 24, 2021 by hgpu

Homomorphic-Encrypted Volume Rendering

Sebastian Mazza

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Tags: Algorithms, AMD Radeon RX 580, ATI, Computer science, GLSL, nVidia, nVidia GeForce RTX 3090, Package, Rendering, Security, Thesis, Visualization, Vulkan

October 17, 2021 by hgpu

Artificial Intelligence in Electric Machine Drives: Advances and Trends

Shen Zhang

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Tags: Algorithms, Artificial intelligence, Computer science, Deep learning, FPGA, nVidia, nVidia Tegra K1, Review

October 17, 2021 by hgpu

Beyond Desktop Computation: Challenges in Scaling a GPU Infrastructure

Martin Uray, Eduard Hirsch, Gerold Katzinger, Michael Gadermayr

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia RTX A6000

October 17, 2021 by hgpu

AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference

Yue Niu, Ramy E. Ali, Salman Avestimehr

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Tags: Computer science, Neural networks, nVidia, nVidia Quadro RTX 5000, Security

October 10, 2021 by hgpu

Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations

Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna

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Tags: Computer science, Deep learning, nVidia, nVidia GeForce GTX 1650

October 10, 2021 by hgpu

GCN Inference Acceleration using High-Level Synthesis

Yi Chien Lin, Bingyi Zhang, Viktor Prasanna

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Tags: Computer science, Data parallelism, Design space exploration, FPGA, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package

October 10, 2021 by hgpu

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

Enhancing Transformer Performance and Portability through Auto-tuning Frameworks

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high performance computing on graphics processing units: hgpu.org

Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

Monitoring Collective Communication Among GPUs

Principal Kernel Analysis: A Tractable Methodology to Simulate Scaled GPU Workloads

OMB-Py: Python Micro-Benchmarks for Evaluating Performance of MPI Libraries on HPC Systems

Least Squares on GPUs in Multiple Double Precision

Homomorphic-Encrypted Volume Rendering

Artificial Intelligence in Electric Machine Drives: Advances and Trends

Beyond Desktop Computation: Challenges in Scaling a GPU Infrastructure

AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference

Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations

GCN Inference Acceleration using High-Level Synthesis

Recent source codes

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

pplx-garden: Perplexity open source garden for inference technology

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

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