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Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs

Xueying Wang, Guangli Li, Xiao Dong, Jiansong Li, Lei Liu, Xiaobing Feng

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan XP, Tesla P4

July 19, 2020 by hgpu

HaoCL: Harnessing Large-scale Heterogeneous Processors Made Easy

Yao Chen, Xin Long, Jiong He, Yuhang Chen, Hongshi Tan, Zhenxiang Zhang, Marianne Winslett, Deming Chen

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Machine learning, nVidia, OpenCL, Tesla P4

May 24, 2020 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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