Software Performance Engineering and Multicore Programming

Software Performance Engineering and Multicore Programming | Udemy
English | Size: 3.69 GB
Genre: eLearning

What you’ll learn
Define Software Performance Engineering
Learn Multicore Computing & Multicore Programming
Understand Parallelization and Cache Complexity
Take a deep-dive into Memory Hierarchy Optimization
Understand Virtual Machines and how they work
Learn Hypervisor Architecture
Define Montgomery’s Trick and its application

A warm welcome to the Software Performance Engineering and Multicore Programming course by Uplatz.

Software Performance Engineering (SPE) is a systematic method for constructing software systems to meet performance objectives. It is a systematic, quantitative approach to the cost-effective development of software systems to meet performance requirements. SPE is a software-oriented approach that focuses on architecture, design, and implementation choices. SPE gives you the information you need to build software that meets performance requirements on time and within budget.

SPE uses quantitative analysis techniques to predict and evaluate performance implications of design and implementation decisions. The process begins early in the software lifecycle and uses quantitative methods to identify satisfactory combinations of requirements and designs, and to eliminate those that are likely to have unacceptable performance, before developers begin implementation. SPE continues through the detailed design, coding, and testing stages to predict and manage the performance of the evolving software, and to monitor and report actual performance against specifications and predictions. SPE methods cover performance data collection, quantitative analysis techniques, prediction strategies, management of uncertainties, data presentation and tracking, model verification and validation, critical success factors, and performance design principles.

SPE provides an engineering approach to performance, eliminating the issues of performance-driven development and fix-it-later. SPE uses model predictions to evaluate trade-offs in software functions versus hardware costs. The models assist developers in controlling resource requirements by selecting architecture and design alternatives with acceptable performance characteristics. They aid in tracking performance throughout the development process and prevent problems from surfacing late in the life cycle (typically during performance and stress testing).

Multicore Programming refers to the approach of creating concurrent systems for deployment on multicore processor and multiprocessor systems. A multicore processor system is a single processor with multiple execution cores in one chip. By contrast, a multiprocessor system has multiple processors on the motherboard or chip. Multicore programming focuses on the following key elements:

Task Parallelism

Data parallelism

Pipelining

Structured grid

Software Performance Engineering and Multicore Programming – Course Curriculum

Software Performance Engineering

Introduction to Multicore Programming

Multithreaded parallelism and Performance Measures

Analysis of Multithreaded Algorithms

Issues in Parallelization

Synchronizing without locks and concurrent data structures

Cache Complexity

Montgomery Trick

Space Vs Time Cache Vs Memory

Experience in coding high performance numeric libraries

FFT Based Polynomial Arithmetic on Multicore

Parallel Programming for Many high-performance Architectures

Memory Hierarchy Optimization-I

Memory Hierarchy Optimization-II

Writing Correct Programs

Floating Point

Applications

Dynamic Scheduling Sorting

Virtual Machines

Hypervisor

Multicore Computing

Multicore Programming-I

Multicore Programming-II

Multicore Programming-III

Multicore Programming-IV

Multicore Programming-V

Who this course is for:
System Performance Engineers
Software Engineers
Newbies & Beginners in the field of Performance Engineering
Anyone aspiring for a career in Software and Performance Engineering
System Engineers & Analysts
System Administrators
Cloud Architects & Engineers
Senior Software Performance Analysis Engineers
Performance Engineers
Software Testers
Embedded Engineers
Safety Performance Engineers
Quality Assurance Leads
Operational Performance Engineers
Electronics & Communication Engineers
Software Developers & Programmers

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