
High Performance Computing
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
This book constitutes the refereed proceedings of the 37th International Conference on High Performance Computing, ISC High Performance 2022, held in Hamburg, Germany, during May 29 - June 2, 2022.
The 18 full papers presented were carefully reviewed and selected from 53 submissions. The papers are categorized into the following topical sub-headings: Architecture, Networks, and Storage; Machine Learning, AI, Emerging Technologies; HPC Algorithms and Applications; Performance Modeling, Evaluation and Analysis; and Programming Environments and Systems Software.
More details
Other editions
Additional editions

Persons
Content
Architecture, Networks, and Storage. Accelerating MPI All-to-All Communication with Online Compression on Modern GPU Clusters.- NVIDIA's Quantum InfiniBand Network Congestion Control Technology and Its Impact on Application Performance.- LLM: Realizing Low-Latency Memory by Exploiting Embedded Silicon Photonics for Irregular Workloads.- SU3_Bench on a Programmable Integrated Unified Memory Architecture (PIUMA) and How that Differs from Standard NUMA CPUs.- Machine Learning, AI, and Emerging Technologies.- "Hey CAI" - Conversational AI Enabled User Interface for HPC Tools.- Hy-Fi: Hybrid Five-Dimensional Parallel DNN Training on High-Performance GPU Clusters.- HPC Algorithms and Applications.- Efficient Application of Hanging-Node Constraints for Matrix-Free High-Order FEM Computations on CPU and GPU.- Dynamic Task Fusion for a Block-Structured Finite Volume Solver over a Dynamically Adaptive Mesh with Local Time Stepping.- Accelerating Simulated Quantum Annealing with GPU and Tensor Cores.- m-Cubes: An Efficient and Portable Implementation of Multi-dimensional Integration for GPUs.- Performance Modeling, Evaluation, and Analysis.- Comparative Evaluation of Call Graph Generation by Profiling Tools.- MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs.- Rapid Execution Time Estimation for Heterogeneous Memory Systems Through Differential Tracing.- Understanding Distributed Deep Learning Performance by Correlating HPC and Machine Learning Measurements.- A Motivating Case Study on Code Variant Selection by Reinforcement Learning.- Programming Environments and System Software.- Remote OpenMP Offloading.- Hybrid Parallel ILU Preconditioner in Linear Solver Library GaspiLS.- A Subset of the CERN Virtual Machine File System: Fast Delivering of Complex Software Stacks for Supercomputing Resources.
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.