LambdaConf 2015 - Introduction to Constraint Logic Programming Sergii Dymchenko
Constraint logic programming is a paradigm that allows solving hard combinatorial problems with minimal programming effort. In this workshop you will learn the basics of the Prolog-based constraint logic programming system ECLiPSe, solve several puzzles, and get hints how constraint logic
From playlist LambdaConf 2015
V4-02. Linear Programming. Definition of the Dual problem.
Math 484: Linear Programming. Definition of the Dual problem. Wen Shen, 2020, Penn State University
From playlist Math484 Linear Programming Short Videos, summer 2020
Constraint Satisfaction Problems in Python
Author David Kopec discusses Constraint-Satisfaction Problems in Python. To learn more, see David's book Classic Computer Science Problems in Python | http://mng.bz/95B1 This video is also available on Manning's liveVideo platform: http://mng.bz/j2wP Use the discount code WATCHKOPEC40 f
From playlist Python
V4-05. Linear Programming. Definition of the Dual problem. Part 4
Math 484: Linear Programming. Definition of the Dual problem. Part 4 Wen Shen, 2020, Penn State University
From playlist Math484 Linear Programming Short Videos, summer 2020
From playlist Parallel Programming Concepts by Dr. Peter Troger
Python as a language has enjoyed a decade of usage in both industry and academia. It has been the most popular abstractions to scientific computing and machine learning, yet the base remains single-threaded. Just how is productivity in these fields being maintained with a single-threaded l
From playlist Python
Stanford Seminar: Time Traveling Hardware and Software Systems
EE380: Computer Systems Colloquium Time Traveling Hardware and Software Systems Srini Devadas , MIT With the imminent demise of Moore's Law, the importance of parallel computing is only increasing. However, efficient parallel computing with ease of programmability still remains elusive. S
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
PROG2006: Programming Paradigms
PROG2006 Advanced Programming Programming Paradigms Coroutines and Concurrent programming Imperative and Structured programming Programming paradigms overview Discussion
From playlist PROG2006 - Programming
21.2.1 Instruction-level Parallelism
MIT 6.004 Computation Structures, Spring 2017 Instructor: Chris Terman View the complete course: https://ocw.mit.edu/6-004S17 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62WVs95MNq3dQBqY2vGOtQ2 21.2.1 Instruction-level Parallelism License: Creative Commons BY-NC-SA
From playlist MIT 6.004 Computation Structures, Spring 2017
EmberConf 2017: State, Time, and Concurrency by Alex Matchneer
State, Time, and Concurrency by Alex Matchneer Modeling changes to state over time is a challenge that most modern app developers have to face. The ember-concurrency addon went a long way toward simplifying many of the challenges inherent in safely modeling asynchronous operations, but th
From playlist EmberConf 2017
Integrating Inference with Stochastic Process Algebra Models - Jane Hillston, Edinburgh
ProPPA is a probabilistic programming language for continuous-time dynamical systems, developed as an extension of the stochastic process algebra Bio-PEPA. It offers a high-level syntax for describing systems of interacting components with stochastic behaviours where some of the parameters
From playlist Logic and learning workshop
PROG2006: Programming Paradigms (and collections)
PROG2006 Advanced Programming Programming Paradigms Quick chat about collections
From playlist PROG2006 - Programming
19.2.1 Interprocess Communication
MIT 6.004 Computation Structures, Spring 2017 Instructor: Chris Terman View the complete course: https://ocw.mit.edu/6-004S17 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62WVs95MNq3dQBqY2vGOtQ2 19.2.1 Interprocess Communication License: Creative Commons BY-NC-SA Mo
From playlist MIT 6.004 Computation Structures, Spring 2017
Synchronous vs Asynchronous Programming
We all learn to program by learning synchronous programming first. We call a function, and our code stops and doesn't do the next thing until we receive a response. The trouble is that as soon as our systems get even a little more complex than that, this complexity explodes. In large-scale
From playlist Software Engineering
Paul-André Melliès - A gentle introduction to template games and linear logic
Game semantics is the art of interpreting formulas (or types) as games and proofs (or programs) as strategies. In order to reflect the interactive behaviour of pro- grams, strategies are required to follow specific scheduling policies. Typically, in the case of a sequential programming lan
From playlist Combinatorics and Arithmetic for Physics: Special Days 2022
Kelsey Hightower On Kubernetes & Cloud Computing | The Engineering Room Ep. 13
"The Engineering Room" is a monthly series of conversations with people who are influential in the software industry. In this episode Dave Farley, author of "Continuous Delivery", "Modern Software Engineering" and others, talks to Google Distinguished Engineer, Kelsey Hightower. Kelsey is
From playlist The Engineering Room
The Rust programming language purports the bold claim that it guarantees thread safety while retaining the ability to write zero-cost abstractions. In this talk we'll explore precisely how Rust can make such a claim. We'll also explore the ecosystem that makes up the concurrency toolkit in
From playlist Rust
V4-04. Linear Programming. Definition of the Dual problem. Part 3
Math 484: Linear Programming. Definition of the Dual problem. Part 3 Wen Shen, 2020, Penn State University
From playlist Math484 Linear Programming Short Videos, summer 2020