Compiler optimizations

Automatic parallelization

Automatic parallelization, also auto parallelization, or autoparallelization refers to converting sequential code into multi-threaded and/or vectorized code in order to use multiple processors simultaneously in a shared-memory multiprocessor (SMP) machine. Fully automatic parallelization of sequential programs is a challenge because it requires complex program analysis and the best approach may depend upon parameter values that are not known at compilation time. The programming control structures on which autoparallelization places the most focus are loops, because, in general, most of the execution time of a program takes place inside some form of loop.There are two main approaches to parallelization of loops: pipelined multi-threading and cyclic multi-threading. For example, consider a loop that on each iteration applies a hundred operations, and runs for a thousand iterations. This can be thought of as a grid of 100 columns by 1000 rows, a total of 100,000 operations. Cyclic multi-threading assigns each row to a different thread. Pipelined multi-threading assigns each column to a different thread. (Wikipedia).

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How to use Parallel Computing in MATLAB

Parallel Computing Toobox™ lets you solve computationally and data-intensive problems using multicore processors, GPUs, clusters, and clouds. Parallel computing is ideal for problems such as parameter sweeps, optimizations, and Monte Carlo simulations. Perform parallel computing concepts u

From playlist “How To” with MATLAB and Simulink

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Application of parallelogram mechanism 3

Transmission of rotation movement between parallel shafts The red disk rotates without fixed bearing. STEP files of this video: http://www.mediafire.com/file/7vae3f0d314e1a8/ApplicationParallel3STEP.zip

From playlist Mechanisms

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Properties of Parallelograms

I introduce the Properties of Parallelograms...the opposite sides are equal, the opposite angles are equal, the consecutive angles are supplementary, and the diagonals bisect each other. I work through four algebraic examples in this video at 4:28 14:30 Find free review test, useful notes

From playlist Geometry

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Automatic Pattern Matching for 3D Geometry in Blender

To help refining the alignment of multiple 3D scans with each other, I have written a new tool for Blender which automatically finds the best fit for mesh objects.

From playlist Random Blender Tests

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Using the properties of parallelograms to solve for the missing diagonals

👉 Learn how to solve problems with parallelograms. A parallelogram is a four-sided shape (quadrilateral) such that each pair of opposite sides are parallel and are equal. Some of the properties of parallelograms are: each pair of opposite sides are equal, each pair of opposite sides are pa

From playlist Properties of Parallelograms

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Parallel vectors

This shows an interactive illustration that explains that parallel vectors can have either the same or opposite directions. The clip is from the book "Immersive Linear Algebra" at http://www.immersivemath.com

From playlist Chapter 2 - Vectors

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What are parallel lines and a transversal

👉 Learn about converse theorems of parallel lines and a transversal. Two lines are said to be parallel when they have the same slope and are drawn straight to each other such that they cannot meet. In geometry, parallel lines are identified by two arrow heads or two small lines indicated i

From playlist Parallel Lines and a Transversal

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Automatic Parallelism

This talk from the Wolfram Technology Conference 2011 gives you a look at advanced features of Mathematica's parallel programming language, including automatic distribution of values to parallel kernels and automatic parallelization of programs. For more information about Mathematica, p

From playlist Wolfram Technology Conference 2011

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Application of parallelogram mechanism 5

Transmission for electric locomotive. There are 3 parallelogram mechanisms. The one connecting the two wheels helps overcome dead positions that may happen to other parallelogram mechanisms. Inventor files of this video: http://www.mediafire.com/file/z1p6ot858n4y412/ApplicationPM5Inv.zip

From playlist Mechanisms

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Determining Two Angles are Consecutive Interior Angles from a Figure

👉 Learn how to identify angles from a figure. This video explains how to solve problems using angle relationships between parallel lines and transversal. We'll determine the solution given, corresponding, alternate interior and exterior. All the angle formed by a transversal with two paral

From playlist Parallel Lines and a Transversal

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How to Upgrade to Gulp 4 - Create default, parallel, series, and watch tasks

:: Support Me :: https://www.patreon.com/alecaddd http://www.alecaddd.com/support-me/ https://amzn.to/2Hcp5mo Try SkySilk VPS: http://bit.ly/2xrm79p Check out Elementor: http://bit.ly/2q10nRo NordVPN: https://go.nordvpn.net/SHqa :: Join the Forum :: https://forum.alecaddd.com/ :: Tutori

From playlist Learn Gulp from Scratch

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Matthijs Vákár: Mathematical foundations of automatic differentiation

HYBRID EVENT Recorded during the meeting "Logic of Probabilistic Programming" the January 31, 2022 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's Aud

From playlist Virtual Conference

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Parallel Computing in the Wolfram Language

In the first webinar of the Software Development webinar series, you'll learn about the state-of-the-art local and global optimization techniques and parallel programming paradigms integrated into the Wolfram Language, along with parallelization fundamentals.

From playlist Software Development Webinar Series

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Live CEOing Ep 338: Language Design in Wolfram Language [Iconizing, Kernel Launching & Autocomplete]

In this episode of Live CEOing, Stephen Wolfram discusses the language design of Wolfram Language functions, some featured are iconizing, parallel kernel launching, and ResourceFunction autocompleting. If you'd like to contribute to the discussion in future episodes, you can participate th

From playlist Behind the Scenes in Real-Life Software Design

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Wolfram Language: Tips for Writing Fast Code

Speaker: Jon McLoone (Nick Gaskill) Video shows how to write faster, more powerful Wolfram Language code. Topics range from using special data types to parallelizing your code. For more training resources, please visit: http://www.wolfram.com/Training/

From playlist Write Faster Code with Wolfram Language Virtual Workshop 2014

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Data Science with Mathematica -- Parallelism

In this video of the Data Science with Mathematica track I demonstrate several features of the parallelism framework of the Mathematica system. I start with basic theory on parallelism itself and then show it can be used very efficiently in the Mathematica system. The playlist for the Da

From playlist Data Science with Mathematica

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23C3: Open Source Machine Translation

Speaker: Christine Corbett Moran From tools, to tricks, to projects: build a translation engine from Klingon to Finnish in an hour Today two revolutions are pushing the machine translation field forward: the open source movement, and the broader application of statistical methods. This

From playlist 23C3: Who can you trust

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Live CEOing Ep 345: RemoteSubmit in Wolfram Language

Stephen Wolfram discusses the design of the RemoteSubmit Wolfram Language function. If you'd like to contribute to the discussion in future videos and livestreams, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram here: https://www.t

From playlist Behind the Scenes in Real-Life Software Design

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What is a parallel universe?

Subscribe to our YouTube Channel for all the latest from World Science U. Visit our Website: http://www.worldscienceu.com/ Like us on Facebook: https://www.facebook.com/worldscienceu Follow us on Twitter: https://twitter.com/worldscienceu

From playlist Science Unplugged: Parallel Universes

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NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Parallelizing Training ...

Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Parallelizing Training of the Kinect Body Parts Labeling Algorithm by Derek Murray Abstract: We present the parallelized implementation of decision forest training as used in Kinec

From playlist NIPS 2011 Big Learning: Algorithms, System & Tools Workshop

Related pages

Polytope model | Loop splitting | Transputer | Speculative multithreading | Source-to-source compiler | SequenceL | Iteration | Loop nest optimization | Automatic vectorization | Aliasing (computing) | Dependence analysis | Scalable parallelism | Alias analysis | Scheduling (computing)