By Yair M. Altman
Accelerating MATLAB functionality goals to right this notion via describing a number of how you can significantly increase MATLAB software velocity. jam-packed with hundreds of thousands of valuable suggestions, it leaves no stone unturned, discussing each element of MATLAB.
Ideal for newbies and execs alike, the e-book describes MATLAB functionality in a scale and intensity by no means ahead of released. It takes a complete method of MATLAB functionality, illustrating a number of how you can reach the specified speedup.
The ebook covers MATLAB, CPU, and reminiscence profiling and discusses a number of tradeoffs in functionality tuning. It describes either the appliance of normal suggestions in MATLAB, in addition to tools which are particular to MATLAB akin to utilizing assorted information varieties or integrated functions.
The booklet covers MATLAB vectorization, parallelization (implicit and explicit), optimization, reminiscence administration, chunking, and caching. It explains MATLAB’s reminiscence version and info the way it might be leveraged. It describes using GPU, MEX, FPGA, and other kinds of compiled code, in addition to innovations for dashing up deployed purposes. It information particular assistance for MATLAB GUI, pictures, and I/O. It additionally stories a wide selection of utilities, libraries, and toolboxes which could aid to enhance performance.
Sufficient details is supplied to permit readers to instantly practice the feedback to their very own MATLAB courses. huge references also are integrated to permit those that desire to extend the therapy of a selected subject to take action simply.
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Extra info for Accelerating MATLAB Performance 1001 Tips to Speed Up MATLAB Programs
1. 2. Introduction to Performance Tuning 21 than generating the same container from scratch on-the-ly, so the application appears much faster and more responsive. Yet another variant of this technique is to enable users to stop the processing in midstream, using some dedicated GUI control that is made available when a long-running task begins. 4 Streaming Data as It Becomes Available Iteratively present data as it becomes available (rather than all at once at the end). This was one of the hard-earned lessons of early Internet Explorer versions that were considered extremely slow in rendering webpages.
This was one of the hard-earned lessons of early Internet Explorer versions that were considered extremely slow in rendering webpages. Much of this perception was due to the fact that HTML tables (on which the vast majority of webpages were based) were not displayed until the very last table element has been downloaded to the browser and processed. 39 In MATLAB, we can update the data presented onscreen, while the information is still streaming or processing. † When updating real time or streaming data, it is important to automatically process the updates wherever possible.
One of the development manager’s responsibilities is to ensure that premature and/or excessive tuning does not occur. When a project starts, we should allocate 3%–5% for the tuning phase. If it takes longer, this could indicate that something is wrong. 3 The Iterative Performance-Tuning Cycle Performance tuning is a repetitive development cycle task that is typically performed following the irst complete pass of development and testing. This ensures that we tune a stable program that works well in all respects excluding speed/responsiveness, rather than a buggy program.
Accelerating MATLAB Performance 1001 Tips to Speed Up MATLAB Programs by Yair M. Altman