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EasyPBR: A Lightweight Physically-Based Renderer

Radu Alexandru Rosu, Sven Behnke

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Tags: 3D Graphics and Realism, Deep learning, nVidia, nVidia GeForce RTX 2060, OpenGL, Package, Python, Rendering, Visualization

December 13, 2020 by hgpu

Bit-level Parallelization of 3DES Encryption on GPU

Kaan Furkan Altınok, Afşin Peker, Alptekin Temizel

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 2060, Package, Security

July 26, 2020 by hgpu

HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism

Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, Young-ri Choi

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Tags: Computer science, CUDA, Data parallelism, Deep learning, GPU cluster, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTX Titan V, nVidia GeForce RTX 2060, nVidia Quadro P 4000, nVidia Titan RTX

May 31, 2020 by hgpu

HLS Portability from Intel to Xilinx: A Case Study

HEXL: Intel Homomorphic Encryption Acceleration Library

Accelerating Encrypted Computing on Intel GPUs

Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

CompilerGym: a library performant reinforcement learning environments for compiler tasks

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

HPCToolkit

Measurement and Analysis of GPU-accelerated Applications with HPCToolkit

NVPTX-SPIR-V Translator

Supporting CUDA for an extended RISC-V GPU architecture

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high performance computing on graphics processing units: hgpu.org

EasyPBR: A Lightweight Physically-Based Renderer

Bit-level Parallelization of 3DES Encryption on GPU

HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism

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