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Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

Shilei Tian, Jon Chesterfield, Johannes Doerfert, Barbara Chapman

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Tags: Computer science, CUDA, HIP, LLVM, MPI, nVidia, OpenMP, Portability, Tesla V100

June 20, 2021 by hgpu

DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications

Hariharan Devarajan, Huihuo Zheng, Anthony Kougkas, Xian-He Sun, Venkatram Vishwanath

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Tags: Benchmarking, Computer science, Deep learning, MPI, Neural networks, Package, TensorFlow

June 6, 2021 by hgpu

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

David Pankratz

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Tags: Computer science, nVidia, nVidia GeForce GTX 1660 Ti, nVidia GeForce RTX 3080, Rasterization, Raytracing, Rendering, Thesis, Visualization, Vulkan

June 6, 2021 by hgpu

Optimization of Heterogeneous Systems with AI Planning Heuristics and Machine Learning: A Performance and Energy Aware Approach

Suejb Memeti, Sabri Pllana

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Tags: Artificial intelligence, Computer science, Heterogeneous systems, Intel Xeon Phi, Machine learning

June 6, 2021 by hgpu

Exploiting co-execution with oneAPI: heterogeneity from a modern perspective

Raúl Nozal, Jose Luis Bosque

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Tags: Computer science, Heterogeneous systems, Intel UHD 630, load balancing, SYCL

June 6, 2021 by hgpu

Early Experiences Migrating CUDA codes to oneAPI

Manuel Costanzo, Enzo Rucci, Carlos García Sanchez, Marcelo Naiouf

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2070, Portability, SYCL

June 6, 2021 by hgpu

Using Workload Characterization to Guide High Performance Graph Processing

Mohamed W. Hassan

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, OpenCL, Optimization, Tesla K20, Thesis

May 30, 2021 by hgpu

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

Keichi Takahashi, Wassapon Watanakeesuntorn, Kohei Ichikawa, Joseph Park, Ryousei Takano, Jason Haga, George Sugihara, Gerald M. Pao

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Tags: Computer science, CUDA, HPC, nVidia, OpenCL, Package, Performance, performance portability

May 30, 2021 by hgpu

Sequence Parallelism: Making 4D Parallelism Possible

Shenggui Li, Fuzhao Xue, Yongbin Li, Yang You

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Tags: Computer science, CUDA, Deep learning, nVidia, Tesla P100

May 30, 2021 by hgpu

TENSILE: A Tensor granularity dynamic GPU memory scheduler method towards multiple dynamic workloads system

Kaixin Zhang, Hongzhi Wang, Tongxin Li, Han Hu, Jiye Qiu, Songling Zou

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Tags: Computer science, CUDA, Databases, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 2080 Ti, Task scheduling

May 30, 2021 by hgpu

cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla A100, Tesla V100

May 30, 2021 by hgpu

Automatically Exploiting the Memory Hierarchy of GPUs through Just-in-Time Compilation

Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos, Christos Kotselidis

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Tags: Benchmarking, Computer science, Java, nVidia, nVidia GeForce GTX 1650, OpenCL, Package

May 23, 2021 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

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high performance computing on graphics processing units: hgpu.org

Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

Optimization of Heterogeneous Systems with AI Planning Heuristics and Machine Learning: A Performance and Energy Aware Approach

Exploiting co-execution with oneAPI: heterogeneity from a modern perspective

Early Experiences Migrating CUDA codes to oneAPI

Using Workload Characterization to Guide High Performance Graph Processing

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

Sequence Parallelism: Making 4D Parallelism Possible

TENSILE: A Tensor granularity dynamic GPU memory scheduler method towards multiple dynamic workloads system

cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Automatically Exploiting the Memory Hierarchy of GPUs through Just-in-Time Compilation

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

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