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This book constitutes the refereed proceedings of the First International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018, held in Seattle, WA, USA, in December 2018. The 20 full papers presented were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections named: AI Benchmarking; Cloud; Big Data; Modelling and Prediction; and Algorithm and Implementations.
This book constitutes the refereed post-conference proceedings of the Third International Symposium on Benchmarking, Measuring, and Optimization, Bench 2020, held virtually in November 2020. The 12 revised full papers and 1 revised short paper presented were carefully reviewed and selected from 28 submissions. The papers are organized in topical sections named: best paper session; data management and storage; supercomputing; benchmarking on GPU; and application and dataset.
This book constitutes the refereed post-conference proceedings of the 14th BenchCouncil International Symposium on Benchmarking, Measuring, and Optimization, Bench 2022, held virtually in November 2022. The 10 revised full papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: Architecture and System, Algorithm and Dataset, Network and Memory.
This book constitutes the refereed proceedings of the Second International Symposium on Benchmarking, Measuring, and Optimization, Bench 2019, held in Denver, CO, USA, in November 2019. The 20 full papers and 11 short papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections named: Best Paper Session; AI Challenges on Cambircon using AIBenc; AI Challenges on RISC-V using AIBench; AI Challenges on X86 using AIBench; AI Challenges on 3D Face Recognition using AIBench; Benchmark; AI and Edge; Big Data; Datacenter; Performance Analysis; Scientific Computing.
This book constitutes the refereed proceedings of the First International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018, held in Seattle, WA, USA, in December 2018. The 20 full papers presented were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections named: AI Benchmarking; Cloud; Big Data; Modelling and Prediction; and Algorithm and Implementations. --
Take your Java programming skills to the next level and learn to overcome real-world challenges to optimize application performance Key Features Leverage key features of the Java Virtual Machine to maximize runtime performance Unlock optimization strategies to effectively manage objects and memory use Apply your knowledge to utilize frameworks and libraries ripe for increasing program performance Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionBuilding high performance into your applications is key to creating an optimal user experience, although it is not the only consideration for the performant nature of your apps. High performance applications can lead to cost-effective resource utilization, especially when scalability and cloud computing are involved. They can also provide highly reliable systems that are easier to maintain. High Performance with Java begins by helping you explore the Java Virtual Machine (JVM) and understand how to push it to its limits to further optimize your programs. You’ll take a hands-on approach to go through memory optimization strategies, input/output operations, concurrency, networking, as well as frameworks and libraries focused on performance. You’ll also learn key strategies and best practices by using industry-relevant examples to architect scalable and resource-efficient applications. The concluding chapters provide valuable insights on optimizing your Java code when interacting with databases and show you how to leverage artificial intelligence (AI) for high performance Java applications. By the end of this book, you’ll grasp the importance of developing high performance Java applications and gain practical experience in implementing key strategies to help ensure your Java applications perform optimally.What you will learn Explore optimization strategies for garbage collection and the JIT compiler Discover best practices when using data structures for high performance Test and compare various approaches to using loops Understand how and when to use object pooling Discern the difference between low-performance and high-performance algorithms Uncover strategies for object creation and immutability to improve performance Gain hands-on experience in avoiding memory leaks Who this book is for This book is for developers, software engineers, and software architects looking to take their Java skills to the next level. Aimed at individuals with a string grasp of Java fundamentals, this book is a practical guide to helping you write high-performing applications.
The Faster Web is quickly changing the way we think about Web development. The Web has changed considerably in recent years and is now built upon many new technologies: the HTTP/2 protocol, asynchronous programming, PHP tools like Blackfire.io and server monitoring tools like the TICK stack. This book will help you take a deep dive into these ...
This book constitutes the thoroughly revised selected papers of the 4th and 5th workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 4 and BPOE 5, held respectively in Salt Lake City, in March 2014, and in Hangzhou, in September 2014. The 16 papers presented were carefully reviewed and selected from 30 submissions. Both workshops focus on architecture and system support for big data systems, such as benchmarking; workload characterization; performance optimization and evaluation; emerging hardware.
This book offers Python programmers one place to look when they needhelp remembering or deciphering the syntax of this open source languageand its many powerful but scantily documented modules. Thiscomprehensive reference guide makes it easy to look up the mostfrequently needed information--not just about the Python languageitself, but also the most frequently used parts of the standard libraryand the most important third-party extensions. Ask any Python aficionado and you'll hear that Python programmers haveit all: an elegant object-oriented language with readable andmaintainable syntax, that allows for easy integration with componentsin C, C++, Java, or C#, and an enormous collection of precoded standardlibrary and third-party extension modules. Moreover, Python is easy tolearn, yet powerful enough to take on the most ambitious programmingchallenges. But what Python programmers used to lack is a concise andclear reference resource, with the appropriate measure of guidance inhow best to use Python's great power. Python in aNutshell fills this need. Python in a Nutshell, Second Edition covers morethan the language itself; it also deals with the mostfrequently used parts of the standard library, and the most popular andimportant third party extensions. Revised and expanded forPython 2.5, this book now contains the gory details of Python's newsubprocess module and breaking news about Microsoft's newIronPython project. Our "Nutshell" format fits Python perfectly bypresenting the highlights of the most important modules and functionsin its standard library, which cover over 90% of your practicalprogramming needs. This book includes: A fast-paced tutorial on the syntax of the Python language An explanation of object-oriented programming in Python Coverage of iterators, generators, exceptions, modules,packages, strings, and regular expressions A quick reference for Python's built-in types and functionsand key modules Reference material on important third-party extensions,such as Numeric and Tkinter Information about extending and embedding Python Python in a Nutshell provides a solid,no-nonsense quick reference to information that programmers rely on themost. This book will immediately earn its place in any Pythonprogrammer's library. Praise for the First Edition: "In a nutshell, Python in a Nutshell serves oneprimary goal: to act as an immediately accessible goal for the Pythonlanguage. True, you can get most of the same core information that ispresented within the covers of this volume online, but this willinvariably be broken into multiple files, and in all likelihood lackingthe examples or the exact syntax description necessary to trulyunderstand a command." --Richard Cobbett, Linux Format "O'Reilly has several good books, of which Python in aNutshell by Alex Martelli is probably the best for giving yousome idea of what Python is about and how to do useful things with it." --Jerry Pournelle, Byte Magazine