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In computer science, program optimization, code optimization, or software optimization is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. [1]
Optimizing software in C++: An optimization guide for Windows, Linux and Mac platforms. This is an optimization manual for advanced C++ programmers. Topics include: The choice of platform and operating system. Choice of compiler and framework. Finding performance bottlenecks.
Optimization in programming is the process of modifying a software system to execute faster and become more efficient by minimizing the use of available computing resources.
In this tutorial, we’ll start with the general definition of optimization. Then, we’ll narrow it down to subject programming optimization. It is one of the essential concepts in computing science.
OR-Tools is an open source software suite for optimization, tuned for tackling the world's toughest problems in vehicle routing, flows, integer and linear programming, and constraint programming.
explore how to make programs run faster via several different types of program optimization. Writing an efficient program requires several types of activ ities. First, we must select an appropriate set of algorithms and data structures. Second, we must write source code that the compiler can effectively optimize to turn into efficient ...
Learn program analysis techniques used in compilers and software development tools to improve productivity, reliability, and security.
We say that code optimization is writing or rewriting code so a program uses the least possible memory or disk space, minimizes its CPU time or network bandwidth, or makes the best use of additional cores. In practice, we sometimes default to another definition: Writing less code.
6.172 is an 18-unit class that provides a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems.
Improving program performance. When and what to optimize. Better algorithms & data structures vs. tuning the code. Exploiting an understanding of underlying system. Compiler capabilities. Hardware architecture. Program execution.