By Yair M. Altman
Accelerating MATLAB functionality goals to right this conception by means of describing a number of how one can enormously increase MATLAB software pace. filled with hundreds of thousands of precious advice, it leaves no stone unturned, discussing each point of MATLAB.
Ideal for newbies and pros alike, the booklet describes MATLAB functionality in a scale and intensity by no means sooner than released. It takes a accomplished method of MATLAB functionality, illustrating quite a few how you can reach the specified speedup.
The booklet covers MATLAB, CPU, and reminiscence profiling and discusses a number of tradeoffs in functionality tuning. It describes either the applying of ordinary recommendations in MATLAB, in addition to equipment which are particular to MATLAB resembling utilizing various facts forms or integrated functions.
The e-book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, reminiscence administration, chunking, and caching. It explains MATLAB’s reminiscence version and information the way it may be leveraged. It describes using GPU, MEX, FPGA, and other kinds of compiled code, in addition to strategies for dashing up deployed purposes. It information particular assistance for MATLAB GUI, portraits, and I/O. It additionally stories a large choice of utilities, libraries, and toolboxes which may support to enhance performance.
Sufficient details is equipped to permit readers to instantly practice the feedback to their very own MATLAB courses. large references also are incorporated to permit those that desire to extend the therapy of a specific subject to take action simply.
Read or Download Accelerating MATLAB Performance 1001 Tips to Speed Up MATLAB Programs PDF
Best mathematical & statistical books
Computing With Mathematica is a student-friendly courseware which equips scholars with the required instruments to exploit Mathematica to resolve difficulties of their engineering, physics, records, arithmetic, or computing device technology classes. As an academic, scholars will make the most of studying on their lonesome tips on how to use Mathematica for problem-solving in technical fields.
"Poisson element techniques presents an summary of non-homogeneous and multidimensional Poisson aspect strategies and their a variety of functions. Readers will locate confident mathematical instruments and functions starting from emission and transmission computed tomography to a number of aim monitoring and allotted sensor detection, written from an engineering viewpoint.
The SAS/ACCESS interface to notebook records allows you to entry and use laptop records speedy and simply. all of the strength and adaptability of SAS can be utilized to investigate and current facts without delay from well known workstation dossier codecs. getting access to notebook documents should be so simple as filling within the blanks, and studying and reporting might be as effortless as pointing and clicking.
The in depth use of computerized facts acquisition method and using cloud computing for strategy tracking have resulted in an elevated prevalence of commercial procedures that make the most of statistical method regulate and power research. those analyses are played virtually completely with multivariate methodologies.
- Space, Structure and Randomness: Contributions in Honor of Georges Matheron in the Fields of Geostatistics, Random Sets and Mathematical Morphology (Lecture Notes in Statistics)
- Hedge Fund Modelling and Analysis using MATLAB
- SAS/GRAPH 9.2 Reference
- Modern Methodology and Applications in Spatial-Temporal Modeling
- Introduction to Information Retrieval and Quantum Mechanics
- Mathematical Explorations with MATLAB
Additional info for Accelerating MATLAB Performance 1001 Tips to Speed Up MATLAB Programs
In fact, if it does not happen, then you have probably not correctly identiied the top bottlenecks according to Pareto’s principle. It is partly due to the diminishing speedups that it is tempting to continue tuning, in the hope that “just a few more rounds” will give us another 50% speedup. But at some point, the cost–beneit ratio of the tuning round simply becomes too high. 2 When to Stop Tuning Following each tuning re-run, we should recheck whether the application is fast enough, and continue tuning only if it is not.
We then modify the code to ix these hotspots, focusing our attentions only at a few top hotspots, using a wide variety of techniques (see Chapters 3 through 11). • We now test the program to ensure that we did not introduce any bugs. This is very important, since we often inadvertently introduce new bugs in the tuning process. 10 Moreover, we should test that the program is actually faster. * No performance improvement is really possible without measurement. ” It is important to measure the correct things, and to do this correctly, without external artifacts that may affect the measurements.
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. Performance tuning includes the following sub-tasks: • We irst measure the overall code performance in order to determine whether tuning is at all necessary.