Found 36 talks width keyword programming language

 PyCOMPSs is a task-based programming in Python that enables simple sequential codes to be executed in parallel in distributed computing platforms. It is based on the addition of python decorators in the functions of the code to indicate those that can be executed in parallel between them. The runtime takes care of the different parallelization and resource management actions, as well as of the ditribution of the data in the different nodes of the computing infrastructure. It is installed in multiple supercomputers of the RES, like MareNostrum 4 and now LaPalma. The talk will present an overview of PyCOMPSs, two demos with simple examples and a hands-on in LaPalma on how we can parallelize EMCEE workloads.

Slides and Examples: https://gitlab.com/makhlaghi/smack-talks-iac

Eclipse Foundation AISBL[1] is the biggest Open Source organization within the EU. It the home for over 400 projects[2] covering a wide range of knowledge areas. It also hosts 18 groups of companies (Working Groups) forming an ecosystem of over 300 organizations[3] that supports the development of many of these projects, as well as the creation of a variety of specifications within different industries.

Eclipse Foundation has a long history of fruitful relations with research and development projects[4] and organizations worldwide, and specifically in Europe.

During this session, an introduction of Eclipse Foundation will be delivered, insisting on our main value proposition, followed by a short description of some of the most relevant projects, especially in the area of Research, in which we are involved.

We will finalise the presentation describing how The Eclipse Foundation interacts with these R&D organizations and institutions as a needed requirement towards exploring together potential collaboration vectors in the near future.

Did you ever want to re-run your project from the beginning, but run into trouble because you forgot one step? Do you want to run just one part of your project and ignore the rest? Do you want to run it in parallel with many different inputs using all the cores of your computer? Do you want to design a modular project, with re-usable parts, avoiding long files hard to debug?

Make is a well-tested solution to all these problems. It is independent of the programming language you use. Instead of having a long code hard to debug, you can connect its components making a chain. Make will allow you to automate your project and retain control of how its parts are integrated. This SMACK seminar will give an overview of this powerful tool.

Gitlab link: https://gitlab.com/makhlaghi/smack-talks-iac/-/tree/master/

We will introduce several ways in which trivially embarrassingly parallel tasks can be run in laptops and desktops. We will introduce command-line tools such as GNU parallel and Kiko. We will then focus on simple techniques for optimisation of scientific computations in python. We will cover parallel computing with multiprocessing, acceleration of functions via numba, and GPU computing with cupy. The goal is to provide an easy roadmap for python code optimisation methods that can applied on already existing code, without writing a single line of C or FORTRAN.

This talk will present an overview of what Latex is, discuss when to  use it and when not, show installing and editing options, introduce classes and packages, and give some usage recommendations and troubleshooting tips.

Pandas is an open source Python package that is widely used for data analysis. It is a powerful ally for data munging/wrangling and databases manipulation/visualisation, and a must-have tool for Data Scientists. In this seminar we will have a general overview on its functionality and we will run over some of the reasons of its large success in the Data Science community.

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 3

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Deep learning
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Data challenges and solutions in forthcoming surveys
Lecture 4