high performance computing on graphics processing units: hgpu.org

Tal Ben-Nun, Linus Groner, Florian Deconinck, Tobias Wicky, Eddie Davis, Johann Dahm, Oliver Elbert, Rhea George, Jeremy McGibbon, Lukas Trümper, Elynn Wu, Oliver Fuhrer, Thomas Schulthess, Torsten Hoefler

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Tags: CUDA, Earth and Space Sciences, nVidia, Python, Tesla A100, Tesla P100, Weather Prediction Model

May 15, 2022 by hgpu

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, Graph theory, nVidia, OpenCL, Package, Performance, SYCL

May 8, 2022 by hgpu

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

Chuan-Chi Wang, Chun-Yen Ho, Chia-Heng Tu, Shih-Hao Hung

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti, Package, Particle swarm optimization

May 8, 2022 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

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high performance computing on graphics processing units: hgpu.org

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

SOL: Reducing the Maintenance Overhead for Integrating Hardware Support into AI Frameworks

Fault Injection techniques for GPU Reliability Evaluation

Lossless Acceleration for Seq2seq Generation with Aggressive Decoding

The Application of AI Technology in GPU Scheduling Algorithm Optimization

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

GPU-based JSON data processing using structural indexes

Productive Performance Engineering for Weather and Climate Modeling with Python

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

cuPSO: GPU Parallelization for Particle Swarm Optimization Algorithms

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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