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Daisen: A Framework for Visualizing Detailed GPU Execution

Yifan Sun, Yixuan Zhang, Ali Mosallaei, Michael D. Shah, Cody Dunne, David Kaeli

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Tags: AMD R9 Nano, Artificial intelligence, ATI, Computer science, CUDA, Hardware Architecture, nVidia, OpenCL, Visualization

April 5, 2021 by hgpu

Performance portability through machine learning guided kernel selection in SYCL libraries

John Lawson

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Tags: AMD R9 Nano, ATI, Auto-Tuning, Benchmarking, Clustering, Computer science, Machine learning, Package, Performance, performance portability, SYCL

September 6, 2020 by hgpu

Towards automated kernel selection in machine learning systems: A SYCL case study

John Lawson

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Tags: AMD R9 Nano, ATI, Computer science, Heterogeneous systems, Machine learning, Package, Performance, SYCL

March 22, 2020 by hgpu

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

Yifan Sun, Trinayan Baruah, Saiful A. Mojumder, Shi Dong, Xiang Gong, Shane Treadway, Yuhui Bao, Spencer Hance, Carter McCardwell, Vincent Zhao, Harrison Barclay, Amir Kavyan Ziabari, Zhongliang Chen, Rafael Ubal, Jose L. Abellan, John Kim, Ajay Joshi

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Tags: AMD R9 Nano, ATI, Computer science, Hardware Architecture, OpenCL, Package, Performance

June 23, 2019 by hgpu

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

John Lawson, Mehdi Goli, Duncan McBain, Daniel Soutar, Louis Sugy

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Tags: AMD R9 Nano, ATI, BLAS, Computer science, Deep learning, Linear Algebra, Machine learning, Mathematical Software, OpenCL, Package, Performance, performance portability, SYCL

April 14, 2019 by hgpu

Evaluating Performance Tradeoffs on the Radeon Open Compute Platform

Yifan Sun, Saoni Mukherjee, Trinayan Baruah, Shi Dong, Julian Gutierrez, Prannoy Mohan, David Kaeli

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Tags: AMD R9 Nano, ATI, Computer science, Heterogeneous systems, HSA, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

April 7, 2018 by hgpu

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David Kaeli, Qianqian Fang

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Tags: Algorithms, AMD R9 Nano, AMD Radeon RX 480, ATI, Computational Physics, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 590, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, OpenCL, Package, Physics

November 12, 2017 by hgpu

Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

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Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

Matthew W. Moskewicz, Ali Jannesari, Kurt Keutzer

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Tags: AMD R9 Nano, ARM, ATI, Code generation, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

November 23, 2016 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

GPU plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Parallel Gaussian process with kernel approximation in CUDA

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