For a long time the techniques of solving linear optimization (LP) problems improved only marginally. Fifteen years ago, however, a revolutionary discovery changed everything. A new `golden age' for optimization started, which is continuing up to the current time. What is the cause of the excitement? Techniques of linear programming formed previously an isolated body of knowledge. Then suddenly a tunnel was built linking it with a rich and promising land, part of which was already cultivated, part of which was completely unexplored. These revolutionary new techniques are now applied to solve conic linear problems. This makes it possible to model and solve large classes of essentially nonlinear optimization problems as efficiently as LP problems. This volume gives an overview of the latest developments of such `High Performance Optimization Techniques'. The first part is a thorough treatment of interior point methods for semidefinite programming problems. The second part reviews today's most exciting research topics and results in the area of convex optimization. Audience: This volume is for graduate students and researchers who are interested in modern optimization techniques.

The hands-on guide to high-performance coding and algorithm optimization. This hands-on guide to software optimization introduces state-of-the-art solutions for every key aspect of software performance - both code-based and algorithm-based. Two leading HP software performance experts offer comparative optimization strategies for RISC and for the new Explicitly Parallel Instruction Computing (EPIC) design used in Intel IA-64 processors. Using many practical examples, they offer specific techniques for: Predicting and measuring performance - and identifying your best optimization opportunities Storage optimization: cache, system memory, virtual memory, and I/0 Parallel processing: distributed-memory and shared-memory (SMP and ccNUMA) Compilers and loop optimization Enhancing parallelism: compiler directives, threads, and message passing Mathematical libraries and algorithms Whether you're a developer, ISV, or technical researcher, if you need to optimize high-performance software on today's leading processors, one book delivers the advanced techniques and code examples you need: Software Optimization for High Performance Computing.

A guide for MySQL administrators covers such topics as benchmarking, server performance, indexing, queries, hardware optimization, replication, scaling, cloud hosting, and backup and recovery.

Optimize the performance of your mobile websites and webapps to the extreme. With this hands-on book, veteran mobile and web developer Maximiliano Firtman demonstrates which aspects of your site or app slow down the user’s experience, and what you can do to achieve lightning-fast performance. There’s much at stake: if you want to boost your app’s conversion rate, then tackling performance issues is the best way to start. Learn tools and techniques for working with responsive web design, images, the network layer, and many other ingredients—plus the metrics to check your progress. Ideal for web developers and web designers with HTML, CSS, JavaScript, and HTTP experience, this is your guide to superior mobile web performance. You’ll dive into: Emulators, simulators, and other tools for measuring performance Basic web performance concepts, including metrics, charts, and goals How to get real data from mobile browsers on your real networks APIs and specs for measuring, tracking and improving web performance Insights and tricks for optimizing the first view experience Ways to optimize post-loading experiences and future visits Responsive web design and its performance challenges Tips for extreme performance to achieve best conversion rates How to work with web views inside native apps

High Performance MySQL is the definitive guide to building fast, reliable systems with MySQL. Written by noted experts with years of real-world experience building very large systems, this book covers every aspect of MySQL performance in detail, and focuses on robustness, security, and data integrity. High Performance MySQL teaches you advanced techniques in depth so you can bring out MySQL's full power. Learn how to design schemas, indexes, queries and advanced MySQL features for maximum performance, and get detailed guidance for tuning your MySQL server, operating system, and hardware to their fullest potential. You'll also learn practical, safe, high-performance ways to scale your applications with replication, load balancing, high availability, and failover. This second edition is completely revised and greatly expanded, with deeper coverage in all areas. Major additions include: Emphasis throughout on both performance and reliability Thorough coverage of storage engines, including in-depth tuning and optimizations for the InnoDB storage engine Effects of new features in MySQL 5.0 and 5.1, including stored procedures, partitioned databases, triggers, and views A detailed discussion on how to build very large, highly scalable systems with MySQL New options for backups and replication Optimization of advanced querying features, such as full-text searches Four new appendices The book also includes chapters on benchmarking, profiling, backups, security, and tools and techniques to help you measure, monitor, and manage your MySQL installations.

Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker