high performance computing on graphics processing units: hgpu.org

hgpu.org » ATI

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

Donald W. Johnson, T. J. Jankun-Kelly

View

Download (PDF)

Tags: AMD Radeon HD 7950, ATI, Computer science, Interactive application, OpenCL, Visualization

May 9, 2021 by hgpu

Daisen: A Framework for Visualizing Detailed GPU Execution

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

View

Download (PDF)

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

April 5, 2021 by hgpu

Porting a sparse linear algebra math library to Intel GPUs

Yuhsiang M. Tsai, Terry Cojean, Hartwig Anzt

View

Download (PDF)

Source codes

Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, HIP, Linear Algebra, nVidia, Package, Performance, Sparse, Sparse matrix, Tesla V100

March 21, 2021 by hgpu

GPGPU Task Scheduling Technique for Reducing the Performance Deviation of Multiple GPGPU Tasks in RPC-Based GPU Virtualization Environments

Jihun Kang, Heonchang Yu

View

Download (PDF)

Tags: AMD Radeon RX 570, ATI, Cloud, Computer science, HPC, OpenCL, Task scheduling, Virtualization

March 21, 2021 by hgpu

Design, Implementation and Test of Efficient GPU to GPU Communication Methods

Stepan Vanecek

View

Download (PDF)

Tags: AMD Radeon Instinct Mi50, ATI, Computer science, Heterogeneous systems, HIP, MPI, nVidia DGX-1, Thesis

January 3, 2021 by hgpu

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Beau Johnston, Jeffrey S. Vetter, Josh Milthorpe

View

Download (PDF)

Source codes

Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, CUDA, Heterogeneous systems, HIP, Matrix multiplication, nVidia, OpenCL, Package, Performance, Tesla P100

November 29, 2020 by hgpu

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

Raúl Nozal, Jose Luis Bosque, Ramon Beivide

View

Download (PDF)

Source codes

Tags: AMD Radeon R7, ATI, Computer science, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX 950, OpenCL, Package, performance portability, Task scheduling

November 1, 2020 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

View

Download (PDF)

Source codes

Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

Performance portability through machine learning guided kernel selection in SYCL libraries

John Lawson

View

Download (PDF)

Source codes

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

September 6, 2020 by hgpu

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Alexander Brauckmann

View

Download (PDF)

Tags: AMD Radeon HD 7970, ATI, Code generation, Computer science, LLVM, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 970, OpenCL, Thesis

July 12, 2020 by hgpu

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Hartwig Anzt, Terry Cojean, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yuhsiang Mike Tsai, Enrique S. Quintana-Ortí

View

Download (PDF)

Source codes

Tags: Algorithms, AMD Radeon VII, ATI, Computer science, CUDA, HIP, Linear Algebra, Mathematical Software, nVidia, Package, Sparse, Sparse matrix, Tesla V100

July 5, 2020 by hgpu

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Yuhsiang M. Tsai, Terry Cojean, Tobias Ribizel, Hartwig Anzt

View

Download (PDF)

Source codes

Tags: AMD Radeon VII, ATI, Computer science, CUDA, Linear Algebra, Mathematical Software, nVidia, Package

June 28, 2020 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_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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

Daisen: A Framework for Visualizing Detailed GPU Execution

Porting a sparse linear algebra math library to Intel GPUs

Design, Implementation and Test of Efficient GPU to GPU Communication Methods

Evaluating the Performance and Portability of Contemporary SYCL Implementations

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

Transparent Acceleration of Java-based Deep Learning Engines

Performance portability through machine learning guided kernel selection in SYCL libraries

Investigating Input Representations and Representation Models of Source Code for Machine Learning

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

Recent source codes

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

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)