The Research Computing Center Seminars

Oct 16, 2:00 PM: Parallel Programming with OpenMP

Sat, 10/13/2018 - 19:04
Abstract: This workshop will give a brief introduction to shared-memory parallel programming using the OpenMP technique. It is designed to give people knowledge of basic parallel programming topics, examples of applying OpenMP to existing problems, and strategies for avoiding common errors and pitfalls. The tutorial will cover the concepts of parallel programming, such as creation of parallel regions, private and shared variables, control of execution threads and runtime library routines. All the topics will be followed by examples of rewriting existing serial codes (in C/C++ and Fortran) into parallel versions with OpenMP technique. Advanced topics, such as parallel speed-up ratios, cache coherence conflicts and OpenMP 3.0 features, will also be discussed briefly in the end. Objectives: Skill of multithreading programming with C/C++ and Fortran Understand shared-memory principles and performance evaluations Level: Introductory Duration: 2 hours Prerequisites: Basic programming skill using C/C++; Basic Linux commands; Github repository: https://github.com/rcc-uchicago/workshop-openmp

Date: October 16, 2018
Time: 2:00 PM - 4:00 PM

See: https://www.eventbrite.com/e/parallel-programming-with-openmp-tickets-49991783771

Oct 23, 2:00 PM: Introduction to Data Visualization

Sat, 10/13/2018 - 19:04
Abstract: Data visualization allows researchers to explore and then display data in ways to help tell a story about it. This workshop will give a brief introduction to data visualization techniques using common Python libraries such as Bokeh and HoloViews. It is designed to help people who have little to no experience or knowledge of basic data visualization methods. The tutorial will begin with an introduction to the concept of data visualization and a discussion of how to design a data visualization workflow. This will be followed by an introduction to useful functions on stereotypical data visualization methods. A hands-on session will be provided as an opportunity for participants to build sample visualizations using example data sets. Objectives: Introduction to basic concepts of data visualization Hands-on examples of data visualization tools using common used Python libraries Level: Introductory Duration: 2 hours Prerequisites: All participants are expected to bring a laptop with a Mac, Linux, or Windows operating system that they have administrative privileges on, and Python and Jupyter Notebooks are already installed. Basic Linux commands; Basic programming skill using Python with Jupyter Notebook Github repository: https://github.com/rcc-uchicago/workshop-IntroDataVisualization/2018Fall

Date: October 23, 2018
Time: 2:00 PM - 4:00 PM

See: https://www.eventbrite.com/e/introduction-to-data-visualization-tickets-49991895104

Nov 13, 2:00 PM: Parallel Programming in Python: Multithreading and Multiprocessing

Sat, 10/13/2018 - 19:04
Abstract: This hands on workshop on scientific parallel programming in python will provide an overview of parallel programming concepts with focus on the symmetric processing model (SMP) using the multiprocessing and threading python packages. Objectives: By the end of the workshop attendees should be able to: Understand the differences between multithreading and multiprocessing and know which tasks are better suited for multithreading or multiprocessing Use threading and multiprocessing packages for appropriately suited tasks. Duration: 2 hours Level: Intermediate Prerequisites: Attendees should have basic familiarity with the python language. An RCC account is helpful but not required. Attendees are expected to bring a laptop. Github repository: https://github.com/rcc-uchicago/scicomp-intro

Date: November 13, 2018
Time: 2:00 PM - 4:00 PM

See: https://www.eventbrite.com/e/parallel-programming-in-python-multithreading-and-multiprocessing-tickets-49992219073

Nov 27, 2:00 PM: Introduction to the Digital Humanities

Sat, 10/13/2018 - 19:04
Abstract: Digital Humanities is a growing, interdisciplinary endeavor aimed at uniting technology and humanistic inquiry. This workshop is a basic theoretical and methodological introduction to using and developing digital toolkits, digital texts, and digital media; we will cover corpus-building, basic text-analysis strategies, digital cartography, web-based development, high-performance computing, and creating custom algorithms and data visualizations. Objectives: A basic theoretical and methodological introduction to using and developing digital toolkits, digital texts, and digital media A basic understanding of corpus-building, text-analysis strategies, digital cartography, web-based development and high-performance computing A basic understanding of how to create custom algorithms and data visualizations Duration: 2 hours Level: Introductory Prerequisites: None. Attendees should bring a laptop if they would like to participate in the hands-on exercises. Data Repository: https://github.com/rcc-uchicago/DH_intro_workshop or http://tharsen.net/DH_sources.zip

Date: November 27, 2018
Time: 2:00 PM - 4:00 PM

See: https://www.eventbrite.com/e/introduction-to-the-digital-humanities-tickets-49992619270

Dec 4, 2:00 PM: Reinforcement learning

Sat, 10/13/2018 - 19:04
Abstract: Reinforcement Learning (RL) has been around since the 1950s but only recently, when it was combined with the power of Deep Learning, has it started to produce amazing practical results. For example, in 2016, the Alpha Go system by DeepMind beat a human world champion in the game of Go. Alpha Go learned to play from scratch without knowing anything about the game. No previous program had ever come close to beating a master of this game. More practical examples where RL can be used are self-driving cars, robotics, etc. In this tutorial, we shall introduce the basic ideas from RL such as policy gradients, deep Q-networks (DQN) and Markov decision processes (MDP). We will use these techniques to train a model to balance a pole on a moving cart and to play Atari games. For hands-on excercises, we shall use OpenAI gym toolkit that provides a wide variety of simulated environments. Level: Advanced Duration: 4 hours Prerequisites: Linux, Python, Deep Learning with Keras (if necessary, prerequisite tutorials can be scheduled at any time)

Date: December 4, 2018
Time: 2:00 PM - 6:00 PM

See: https://www.eventbrite.com/e/reinforcement-learning-tickets-49992797804

Oct 30, 2:00 PM: Introduction to R for data analysis

Wed, 10/10/2018 - 10:22
Abstract:The R computing environment has become one of the most important tools in quantitative research, from computational biology to financial modeling. This short workshop will expose participants to the basic elements of R through a hands-on analysis of the Divvy bike trip data. No previous programming experience is required. The aim is to provide participants with the basic tools to analyze data in R or RStudio, either on the RCC cluster, or on their own computer. Specific skills participants will learn include importing data from CSV files, summarizing and processing data in data frames, installing and using R packages, and plotting data using ggplot2. Objectives: (1) work through a basic data analysis in R; (2) understand how to import data from a CSV file into an R data frame; (3) use standard tools to summarize and manipulate data frames; (3) learn how to install and use R packages; (4) use ggplot2 to create plots from data frames; (5) learn through “live coding.” Level: Introductory. Prerequisites: All participants are expected to bring a laptop with a Mac, Linux, or Windows operating system that they have administrative privileges on. An RCC account is helpful, but not required. Github repository: https://github.com/rcc-uchicago/R-intro-divvy

Date: October 30, 2018
Time: 2:00 PM - 5:00 PM

See: https://www.eventbrite.com/e/introduction-to-r-for-data-analysis-tickets-49992009446

Nov 6, 2:00 PM: Introduction to machine learning

Wed, 10/10/2018 - 10:22
Abstract: Machine learning has received more attention as the popularity of data science and big data has grown. The application of machine learning can span from social science to engineering to medicine, performing tasks such as natural language processing, classification, and clustering. In this workshop, participants will learn about the basics of machine learning and supervised versus unsupervised learning algorithms. Participants will have a chance to implement simple machine learning algorithms in python. Objectives: Learners will be able to explain the differences between various machine learning algorithms Learners will be able to use Python’s machine learning packages Learners will be able to load some data (such as Iris, real-estate price, and spam email) and apply various classification and prediction algorithms Level: Introductory Duration: 2 hours Prerequisite: All participants are expected to bring a laptop with a Mac, Linux, or Windows operating system that they have administrative privileges on. If participants do not have an RCC account, they will need to install Anaconda3 on their laptops. Familiarity with python programming is required. Github repository: https://github.com/rcc-uchicago/ml-intro

Date: November 6, 2018
Time: 2:00 PM - 4:00 PM

See: https://www.eventbrite.com/edit?eid=49992102725