From playlist Week 6 2015 Shorts
Array Variables - Introduction
This video introduces array variables. It defines an array variable as a named group of contiguous memory locations, each element of which can be accessed by means of an index number. It explains the difference between one dimensional and two dimensional arrays, and covers how these can
From playlist Data Structures
Linear Algebra: Redundant Vectors and How to Find a Minimal Generating Set
Linear Algebra: Redundant Vectors and How to Find a Minimal Generating Set
From playlist Linear Algebra
Dynamic Random Access Memory (DRAM). Part 1: Memory Cell Arrays
This is the first in a series of computer science videos is about the fundamental principles of Dynamic Random Access Memory, DRAM, and the essential concepts of DRAM operation. This particular video covers the structure and workings of the DRAM memory cell. That is, the basic unit of st
From playlist Random Access Memory
Sets might contain an element that can be identified as an identity element under some binary operation. Performing the operation between the identity element and any arbitrary element in the set must result in the arbitrary element. An example is the identity element for the binary opera
From playlist Abstract algebra
Dynamic Random Access Memory (DRAM). Part 3: Binary Decoders
This is the third in a series of computer science videos is about the fundamental principles of Dynamic Random Access Memory, DRAM, and the essential concepts of DRAM operation. This video covers the role of the row address decoder and the workings of generic binary decoders. It also expl
From playlist Random Access Memory
How PNG Works: Compromising Speed for Quality
Visit https://brilliant.org/Reducible/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription. Chapters: 0:00 Introduction 1:35 Exploiting redundancy 2:09 Huffman Codes 4:22 Run Length Encoding 5:23 Lempel-Ziv Schemes (LZSS) 13:
From playlist Data Compression
From playlist Week 5 2015 Shorts
How we are making Python 3.11 faster (CPython project)
The "Faster CPython" project aims to speed up Python, specifically CPython, by a large factor over the next few releases. The first release to see the benefits of this work is Python 3.11. Python 3.11 includes the following major changes: * Adaptive specializing interpreter (PEP 659) * C
From playlist Python
Stanford Seminar - Accelerating ML Recommendation with over a Thousand RISC-V/Tensor Processors...
Dave Ditzel is the founder and executive Chairman of Esperanto Technologies Inc. This talk was given on March 2, 2022. TAccelerating ML Recommendation with over a Thousand RISC-V/Tensor Processors on a 7nm Chip To accelerate Machine Learning Recommendation and other workloads, Esperant
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Independent Vertex Sets | Graph Theory, Maximal and Maximum Independent Sets
What are independent vertex sets in graph theory? We'll go over independent sets, their definition and examples, and some related concepts in today's video graph theory lesson! A subset of the vertex set of a graph is an independent vertex set if and only if it contains no pair of adjace
From playlist Set Theory
MountainWest RubyConf 2015 - Better Routing Through Trees
by Jeremy Evans This presentation will describe an approach to routing web requests efficiently through the use of a routing tree. A routing tree usually routes requests by looking at the first segment in request path, and sending it to the routing tree branch that handles that segment, re
From playlist MWRC 2015
Jerome Darbon - Algorithms for Non-Local Filtering; application CryoElectron & biological microscopy
Recorded 15 September 2022. Jerome Darbon of Brown University presents "Efficient algorithms for Non-Local Filtering and applications to Cryo-Electron microscopy and biological microscopy" at IPAM's Computational Microscopy Tutorials. Abstract: We present fast and scalable algorithms for n
From playlist Tutorials: Computational Microscopy 2022
Stanford Seminar - Computing with FPGAs - Oskar Mencer
Oskar Mencer Lucent / Bell Labs and Imperial College, London May 2, 2001 Field-Programmable Gate Arrays (FPGAs) can outperform microprocessors on certain tasks by many orders of magnitude. The open research problems of computing with FPGAs arc: (1) understanding the limitations of FPGAs
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Graph Representation part 03 - Adjacency List
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have talked about Adjacency List representation of Graph and analyzed its time and space complexity of adjacency list representation. Previous Lesson:
From playlist Data structures
Advanced Programming with the Wolfram Compiler
The Wolfram Compiler is a long-term project for the compilation of Wolfram Language programs. It converts Wolfram Language into native machine code and provides a faster execution path as well as many opportunities for innovative programming features. It is used for an increasing amount of
From playlist Wolfram Technology Conference 2021
Game Programming Patterns part 17.1 - (Reading, JS) Event Queue
We read through the Event Queue chapter of the Game Programming Patterns book and translate the code examples to JavaScript. Links code - https://github.com/brooks-builds/learning_game_design_patterns twitter - https://twitter.com/brooks_patton book - http://gameprogrammingpatterns.ocm/
From playlist Game Programming Patterns Book
From playlist Mathematics of Sharing
The Fastest Way to Loop in Python - An Unfortunate Truth
What's faster, a for loop, a while loop, or something else? We try several different ways to accomplish a looping task and discover which is fastest. ― mCoding with James Murphy (https://mcoding.io) Source code: https://github.com/mCodingLLC/VideosSampleCode SUPPORT ME ⭐ --------------
From playlist How Python Works