Author: Adam Thomas McLaughlin
Publisher:
ISBN:
Category : Graph algorithms
Languages : en
Pages :
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Book Description
Graph traversal represents an important class of graph algorithms that is the nucleus of many large scale graph analytics applications. While improving the performance of such algorithms using GPUs has received attention, understanding and managing performance under power constraints has not yet received similar attention. This thesis first explores the power and performance characteristics of breadth first search (BFS) via measurements on a commodity GPU. We utilize this analysis to address the problem of minimizing execution time below a predefined power limit or power cap exposing key relationships between graph properties and power consumption. We modify the firmware on a commodity GPU to measure power usage and use the GPU as an experimental system to evaluate future architectural enhancements for the optimization of graph algorithms. Specifically, we propose and evaluate power management algorithms that scale i) the GPU frequency or ii) the number of active GPU compute units for a diverse set of real-world and synthetic graphs. Compared to scaling either frequency or compute units individually, our proposed schemes reduce execution time by an average of 18.64% by adjusting the configuration based on the inter- and intra-graph characteristics.
Author: Yue Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The other technique targets on maximizing the average throughput of all parallel processors under the dynamic power constraints. We formalize this target as a linear programming problem and solve it on the runtime. According to the simulation results, the first technique achieves more than 22% power savings with a 4% improvement in performance and the second technique saves 11% power consumption with 9% performance improvement. The contributions of this dissertation represent a significant advancement in the quest for improving performance and reducing energy consumption of GPGPU.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Abstract : Parallel graph processing is central to analytical computer science applications, and GPUs have proven to be an ideal platform for parallel graph processing. Existing GPU graph processing frameworks present performance improvements but often neglect two issues: the unpredictability of a given input graph and the energy consumption of the graph processing. Our prototype software, EEGraph (Energy Efficiency of Graph processing), is a flexible system consisting of several graph processing algorithms with configurable parameters for vertex update synchronization, vertex activation, and memory management along with a lightweight software-based GPU energy measurement scheme. We observe relationships between different configurations of our software, performance, and GPU energy for processing in-memory and out-of-memory graphs. The ideal parameters are discovered for specific input graphs by analyzing the observed relationships. We also present the utility of subgraph generation to predict the performance and energy consumption of complete graph configurations. EEGraph improves upon state-of-the-art GPU-based graph processing software by 2.08 times for performance and 1.60 times for GPU energy for processing in-memory graph datasets. Additionally, EEGraph improves upon the state-of-the-art by 3.30 times for performance and 1.63 times for GPU energy for processing large out-of-memory graph datasets.
Author: Matt Pharr
Publisher: Addison-Wesley Professional
ISBN: 9780321335593
Category : Computers
Languages : en
Pages : 814
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Book Description
More useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.
Author: Nimish Shah
Publisher: Springer Nature
ISBN: 3031331362
Category : Technology & Engineering
Languages : en
Pages : 155
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Book Description
This book focuses on the acceleration of emerging irregular sparse workloads, posed by novel artificial intelligent (AI) models and sparse linear algebra. Specifically, the book outlines several co-optimized hardware-software solutions for a highly promising class of emerging sparse AI models called Probabilistic Circuit (PC) and a similar sparse matrix workload for triangular linear systems (SpTRSV). The authors describe optimizations for the entire stack, targeting applications, compilation, hardware architecture and silicon implementation, resulting in orders of magnitude higher performance and energy-efficiency compared to the existing state-of-the-art solutions. Thus, this book provides important building blocks for the upcoming generation of edge AI platforms.
Author: Alberto Sangiovanni-Vincentelli
Publisher: Springer Science & Business Media
ISBN: 1461438799
Category : Technology & Engineering
Languages : en
Pages : 219
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Book Description
This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems. The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.
Author: Linghe Kong
Publisher: Elsevier
ISBN: 012819085X
Category : Science
Languages : en
Pages : 440
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Book Description
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. Bridges the gap between radio astronomy and computer science Includes coverage of the observation lifecycle as well as data collection, processing and analysis Presents state-of-the-art research and techniques in big data related to radio astronomy Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)
Author: John Cheng
Publisher: John Wiley & Sons
ISBN: 1118739329
Category : Computers
Languages : en
Pages : 528
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Book Description
Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the "hard" and "soft" aspects of GPU programming. Computing architectures are experiencing a fundamental shift toward scalable parallel computing motivated by application requirements in industry and science. This book demonstrates the challenges of efficiently utilizing compute resources at peak performance, presents modern techniques for tackling these challenges, while increasing accessibility for professionals who are not necessarily parallel programming experts. The CUDA programming model and tools empower developers to write high-performance applications on a scalable, parallel computing platform: the GPU. However, CUDA itself can be difficult to learn without extensive programming experience. Recognized CUDA authorities John Cheng, Max Grossman, and Ty McKercher guide readers through essential GPU programming skills and best practices in Professional CUDA C Programming, including: CUDA Programming Model GPU Execution Model GPU Memory model Streams, Event and Concurrency Multi-GPU Programming CUDA Domain-Specific Libraries Profiling and Performance Tuning The book makes complex CUDA concepts easy to understand for anyone with knowledge of basic software development with exercises designed to be both readable and high-performance. For the professional seeking entrance to parallel computing and the high-performance computing community, Professional CUDA C Programming is an invaluable resource, with the most current information available on the market.
Author:
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 238
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Book Description
Performance tuning is becoming more important than it has been for the last 40 years. Read this book to understand your application's performance that runs on a modern CPU and learn how you can improve it. The 170+ page guide combines the knowledge of many optimization experts from different industries.
Author: Shaoshan Liu
Publisher: Springer Nature
ISBN: 3031213955
Category : Computers
Languages : en
Pages : 360
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Book Description
This book constitutes the proceedings of the 19th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2022, which was held in Jinan, China, during September 24-25, 2022. The 23 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: computer architecture; cloud computing; deep learning; emerging applications; and storage and IO.
