Analysis of parallel algorithms
In parallel computing, granularity (or grain size) of a task is a measure of the amount of work (or computation) which is performed by that task. Another definition of granularity takes into account the communication overhead between multiple processors or processing elements. It defines granularity as the ratio of computation time to communication time, wherein, computation time is the time required to perform the computation of a task and communication time is the time required to exchange data between processors. If is the computation time and denotes the communication time, then the Granularity G of a task can be calculated as: Granularity is usually measured in terms of the number of instructions executed in a particular task. Alternately, granularity can also be specified in terms of the execution time of a program, combining the computation time and communication time. (Wikipedia).
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
Duality and perpendicularity | Universal Hyperbolic Geometry 9 | NJ Wildberger
Perpendicularity in universal hyperbolic geometry is defined in terms of duality. One big difference with classical HG is that points can also be perpendicular, not just lines. Once we have perpendicularity, we can define altitudes. We also state the collinear points theorem and concurrent
From playlist Universal Hyperbolic Geometry
What are the properties that make up a parallelogram
👉 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
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
In this video we continue discussing congruences and, in particular, we discuss solutions of linear congruences. The content of this video corresponds to Section 4.4 of my book "Number Theory and Geometry" which you can find here: https://alozano.clas.uconn.edu/number-theory-and-geometry/
From playlist Number Theory and Geometry
Lec 5 | MIT 6.189 Multicore Programming Primer, IAP 2007
Lecture 5: Parallel programming concepts License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu Subtitles are provided through the generous assistance of Rohan Pai.
From playlist MIT 6.189 Multicore Programming Primer, January (IAP) 2007
Skew Lines, Perpendicular & Parallel Lines & Planes, Intersecting Lines & Transversals
This geometry video tutorial provides a basic introduction into skew lines. It explains the difference between parallel lines, perpendicular lines, skew lines, intersecting lines, and transversals. Parallel lines are coplanar lines that do not intersect. Skew lines are noncoplanar lines
From playlist Geometry Video Playlist
Multivariable Calculus: Find the volume of the parallelepiped based at the origin with adjacent sides as position vectors (1,2,3), (1,0,2), and (0,5,6). This provides an application of the triple product. For more videos like this one, please visit the Multivariable Calculus playlist
From playlist Calculus Pt 7: Multivariable Calculus
Tim Harris: "Systems Challenges in Graph Analytics"
The Turing Lectures: Industrial & Commercial - Tim Harris – Oracle Laboratories: Systems Challenges in Graph Analytics Click the below timestamps to navigate the video. 00:00:10 Introduction by Professor Chris Williams, Edinburgh University 00:01:49 Tim Harris – Oracle Laboratories: Syst
From playlist Turing Lectures
Stanford Seminar - Tiny functions for codecs, compilation, and (maybe) soon everything
EE380: Computer Systems Colloquium Seminar Tiny functions for codecs, compilation, and (maybe) soon everything Speaker: Keith Winstein, Stanford Computer Science Networks, applications, and media codecs frequently treat one another as strangers. By expressing large systems as compositions
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
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
QRM 10-3: The Model Building Approach
This video is taken from by basic RM course and deals with MR under the model-building approach.
From playlist Quantitative Risk Management
Risk Management Lesson 9B: Model-Building Approach to Market Risk
The second part of Lesson 9 still deals with Market Risk, but we discuss the model-building approach, in which we assume a model for our market variables. In particular we consider the so-called Var-Cov approach, which strongly relies on normality (a definitely unrealistic assumption, yet.
From playlist Risk Management
Lecture 13: Object Detection, Recognition and Pose Determination, PatQuick (US 7,016,539)
MIT 6.801 Machine Vision, Fall 2020 Instructor: Berthold Horn View the complete course: https://ocw.mit.edu/6-801F20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63pfpS1gV5P9tDxxL_e4W8O In this lecture, we look at general problems for object detection and pose estima
From playlist MIT 6.801 Machine Vision, Fall 2020
Lec 6 | MIT 6.189 Multicore Programming Primer, IAP 2007
Lecture 6: Design patterns for parallel programming I View the complete course materials: http://ocw.mit.edu/6-189IAP07 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu Subtitles are provided through the generous assistance
From playlist MIT 6.189 Multicore Programming Primer, January (IAP) 2007
This geometry video tutorial provides a basic introduction into parallelograms. It explains the properties of parallelograms and how to use it calculate the missing sides and missing angles of parallelograms. It contains plenty of examples and practice problems for you to work on. Oppo
From playlist Geometry Video Playlist
N Rigid-body Dynamics - Derek Richardson
N Rigid-body Dynamics Derek Richardson University of Maryland July 17, 2009
From playlist PiTP 2009