Leading Data Science faculty serve as instructors for the Data Science Boot Camp at Rice University. The curriculum covers topics ranging from R, Python, Cloud Computing, Unsupervised and Supervised Learning to Deep Learning. Using Rice’s shared computing infrastructure, hands on laboratory sessions supported by the instructor and lab assistants, will be offered each day allowing participants to practice what is being taught in the class sessions.

Prerequisites: Participants should have some previous exposure to basic probability, statistics, linear regression, matrix and vector notation, as well as some familiarity with R and Python programming languages.

Rice Data Science Boot Camp

Leading HPC faculty and staff members from Rice University serve as instructors for the HPC Boot Camp. The curriculum covers topics ranging from MPI, OpenMP, Pthreads, Performance analysis (HPCToolkit), accelerated computing using GPGPU (OpenACC and CUDA), and GPU programming including Numba, Tensorflow and domain-specific CUDA libraries. Using Rice’s shared computing infrastructure, hands on laboratory sessions supported by the instructor and lab assistants, will be offered each day allowing participants to practice what is being taught in the class sessions.

Prerequisites: Participants should be comfortable with using Linux command line for program development and compiling. You should have basic knowledge of development and debugging of sequential programs in C/C++ and/or Fortran.

Rice HPC Boot Camp

The Argonne Training Program on Extreme-Scale Computing (ATPESC) provides intensive, two weeks of training on the key skills, approaches, and tools to design, implement, and execute computational science and engineering applications on current high-end computing systems and the leadership-class computing systems of the future.

As a bridge to that future, this two-week program fills the gap that exists in the training computational scientists typically receive through formal education or other shorter courses. With around 65 participants accepted each year, admission to the ATPESC program is highly competitive. ATPESC is part of the Exascale Computing Project, a collaborative effort of the DOE Office of Science and the National Nuclear Security Administration.

Important Dates

Feb. 28, 2018 – Deadline for applicant submissions
April 16, 2018 – Notification of acceptance
April 27, 2018 – Registration deadline for accepted applicants
May 4, 2018 – Registration deadline for wait-listed applicants

Argonne Training Program on Extreme-Scale Computing (ATPESC)

Cornell Virtual Workshop training topics are available at the Extreme Science and Engineering Discovery Environment (XSEDE) user portal.

The following are the latest additions:

Introduction to Jetstream
Getting Started on KNL (Knights Landing)
Case Study: Profiling and Optimization on KNL Clusters
ParaView – Advanced

Cornell Virtual Workshop topics are freely available at all times to the entire scientific community – researchers, HPC practitioners, students, and educators

On-Demand Training for Jetstream, Knights Landing, and ParaView

A GPU Hackathon is an organized workshop that teams up programmers at all experience levels with experts to facilitate sharing of knowledge and skills in GPU programming. Teams of software developers can come to a hackathon with existing code they want to accelerate on GPUs. Expert mentors help teams develop a plan to port or optimize their code before the start of the workshop. During the one-week coding sprint, teams work with their mentors to transition code to the GPU and achieve software performance goals. This hands-on approach is increasing the number of new GPU programmers and promotes

2018 GPU Hackathons