The Workshop Registration includes access to a choice of two quarter-day Workshops or one half-day Workshop on Monday morning and/or one full-day Workshop on Wednesday. You will be asked to specify your choices during registration.
Monday, March 2 (8:15 AM – Noon)
Includes breakfast, break, and lunch.
Monday, Option 1 (Part 1/2)
Workshop A: Analyzing CPU and GPU Application performance with HPCToolkit
Presented by: John Mellor-Crummey, Professor, Computer Science & ECE, Rice University
Abstract: Tailoring applications for GPU-accelerated compute nodes is essential to harness the power of current and forthcoming GPU-accelerated platforms. Application developers need effective tools for this purpose.
While NVIDIA and others provide tools for performance measurement and analysis, they fall short in providing what application developers need, especially for programs developed using OpenMP offloading and template-based programming models for GPUs.
This tutorial will (1) introduce new capabilities for performance measurement and analysis of GPU-accelerated codes that are emerging Rice University’s HPCToolkit performance tools and (2) describe how to use them to analyze and tune GPU-accelerated applications.
To support efficient monitoring of accelerated computations, HPCToolkit employs a novel wait-free data structures to coordinate measurement and attribution of performance metrics while a GPU-accelerated computation executes. To help developers understand the performance of accelerated applications as a whole, HPCToolkit tool attributes metrics to rich heterogeneous calling contexts that span both CPUs and GPUs and displays traces that include both CPU and GPU activity time lines. To help developers understand the performance of complex GPU code generated from high-level programming models such as OpenMP or template-based programming abstractions, HPCToolkit constructs sophisticated approximations of call path profiles for GPU computations from flat PC samples collected by NVIDIA GPUs. To support fine-grain analysis and tuning, HPCToolkit uses GPU PC samples to derive and attribute metrics, including measures of GPU latency and throughput at all levels in a heterogeneous calling context.
To make effective use of HPCToolkit for tuning GPU-accelerated applications, one must understand what performance metrics that HPCToolkit can collect, and how to use them to guide analysis and tuning.
This tutorial will show how to use HPCToolkit to measure and analyze the performance of GPU-accelerated programs. We will illustrate the capabilities of HPCToolkit with case studies of various codes and mini-applications.
Monday, Option 1 (Part 2/2)
Workshop B: WHPC Roundtable: Growing a Diverse Talent Pool in HPC for Oil & Gas
Presented by: Texas Women in High Performance Computing
- Cristina Beldica, Intel Corporation
- Priscilla Black, consultant
- Carolyn Devany, Data Vortex Technologies
- Melyssa Fratkin, TACC
- Amy Rueve, BP America
- Soumya Seetharam, Anadarko
- Beverly Jurenko, formerly Anadarko (Moderator)
Abstract: This session, organized by Texas Women in HPC (TXWHPC), will be a roundtable discussion of the challenges of growing and retaining a diverse talent pool in the oil & gas industry. Experts from the oil & gas and computing industries, academia, and the national labs will discuss the issues of diversity, inclusion, and retention, share success stories, and offer suggestions for real solutions. Realistically increasing diversity in the workplace requires careful planning and support at all levels.
Monday, Option 2
Workshop C: Best Practices in Supercomputing Systems Management
Presented by: Practitioners and Experts from Industry, Academia, and National Labs
Wednesday, March 4 (8:15 AM – 3:45 PM)
Includes breakfast, morning break, lunch, and afternoon break.
Wednesday, Option 1
Workshop D: From Zero-to-Devito
Presented by: Dr. Gerard Gorman, Dr. Fabio Luporini, Dr. Rhodri Nelson, Mr. Navjot Kukreja, Imperial College London
- Bring a laptop with a browser.
- Basic knowledge of Python programming.
- Basic knowledge of Git and GitHub account.
- Basic knowledge of finite differences.
- Afternoon session:
- Experience with C/C++.
- Experience with OpenMP/OpenACC (or equivalent).
- We also encourage participants to join our slack channel (https://www.devitoproject.org) to make it easier to respond to individual questions.
Abstract: The Devito workshop will consist of a morning session where participants will learn how to implement finite difference and inverse solvers using Devito. The workshop will be in Jupyter notebook which can be either installed on the participants laptops or run directly on a BinderHub instance provided for the workshop. The afternoon session will be run hackathon style, giving experienced HPC developers the opportunity to develop the Devito JIT-escape hatch (ie directly customizing the Devito generated source code), where the target problem is performance optimization of Devito on GPU processors running on Azure Cloud.
Wednesday, Option 2
Workshop E: HPC in the Cloud Tutorial
Presented by: Pierre-Yves Aquilanti, Ph.D., Matt Koop, Stephen Sachs, Amazon Web Services
Attendee Needs:
Attendees will need to come with a laptop or tablet with a keyboard with Wifi. The hands-on can be done through the web browser and accounts will be provided for the day with no setup time required.
Abstract: Cloud computing technologies have rapidly matured and nearly all HPC production workloads can now be efficiently accommodated in a cloud environment. Cloud computing presents a wide array of services and the ability to accommodate the most demanding computational workloads at scale. However, the complexity and scale that comes with such an environment also can make the first experience a daunting proposition.
During this tutorial, attendees will be introduced to compute, storage, and network technologies offered by AWS and demonstrate how to best utilize them in HPC workflows. This will be followed by a deep dive on the computational capabilities offered by cloud computing and, in particular, autoscaling and serverless computing. An overview of storage and network will be provided with a discussion on optimizing for object storage or parallel file systems.
This tutorial will be composed of presentations and hands-on sessions where attendees will have the opportunity to put into practice their learnings on the AWS cloud. A laptop with a wifi connection is required for the hands-on portions of this tutorial. No prior cloud experience is required, but participants will need minimal comfort with the Linux command line interface. AWS accounts will be provided.
