COE HPC

Bring High Performance Computing to Everyone in College of Engineering at Texas A&M University!

News

Online Workshop: NVIDIA Deep Learning Institute for Computer Vision

Posted on by

The NVIDIA Deep Learning Institute (DLI), the Hewlett Packard Enterprise Data Science Institute at the University of Houston, the Texas A&M Institute of Data Science, Texas A&M High Performance Research Computing, and the Texas Engineering Experiment Station invite you to attend an online deep learning workshop on Aug 24, 2020 from 1:00PM to 5:00PM exclusively for verifiable academic students, staff, and researchers. NVIDIA DLI offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.

This workshop is hosted by Dr. Jian Tao through the NVIDIA University Ambassador Program at Texas A&M University.

See the workshop website for further details including how to register.

A Virtualized Environment For Developing Level 4 Autonomous Vehicles

Posted on by


We are kickstarting a new AggiE_Challenge project on autonomous vehicles and training environment simulation at the College of Engineering in Fall 2020.

The primary goals are to create a high-fidelity simulation environment for training and testing autonomous vehicles and build a digital twin of a self-driving vehicle. Additionally, we are training students to join the 2nd round of the GM/SAE Autodrive Challenge (http://autodrive.tamu.edu/) that will likely take place later this year or early next year.

The course is listed on Howdy! with CRN #43979. If you know any undergraduate engineering students who might be interested in it, please feel free to ask them to contact Jian Tao directly. We have up to 20 spots available. A public announcement will be sent out at some point in Aug to attract more students if it is necessary.

TAMIDS seeking student worker in data visualization

Posted on by

The Texas A&M Institute of Data Science (TAMIDS) seeks to hire a student worker with experience in data visualization to assist with various projects.

Data Visualization Trainee

Description

The Texas A&M Institute of Data Science (TAMIDS) is looking for a student worker on data visualization to help with various ongoing data science projects at TAMIDS. Data visualization is the graphical representation of data and it presents the trends, outliers and patterns in the data sets with visual elements like charts, graphs, and maps. Data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions.

Key Responsibilities:

  1. Engage project teams to understand project needs/requirements and provide technical expertise with data visualization tools;
  2. Collaborate with project leaders and multi-discipline teams to design and develop the visualization components of the data science projects;
  3. Work with team members to design and build pipelines for data science projects and automate data visualization processes;
  4. Contribute to technical reports and publications.

Qualifications

We are also looking for an undergraduate student who is 

  • experienced in data analytics and visualization;
  • familiar with data visualization software and script program languages (SQL, Python, R, etc.);
  • eager to learn/develop and bring in emerging trends/technology.

Interested students should send email to Dr. Jian Tao, jtao@tamu.edu, including their resume and
attachments or URLs giving examples of any relevant previous work. Further information concerning
TAMIDS and its Data Science Trainee Program can be found at https://tamids.tamu.edu.

TAMIDS Data Science Webinar Series

Posted on by

The Texas A&M Institute of Data Science invites you to attend the TAMIDS Data Science Webinars from Apr 1 to Apr 15, 2020. This webinar series is to introduce the fundamentals of data science (with python) to students and researchers from the Texas A&M University system.

Registration: FREE

More information of the webinars can be found at

https://tinyurl.com/uwx2dpo

Exascale Computing Project (ECP) Sponsored Training Activities 

Posted on by

March 18 IDEAS-ECP Webinar: Testing Strategies

April 20-24 OpenMP Hackathon

April 21-24 Kokkos Bootcamp and Training

Other Training Activities of Interest 

March 9 NVIDIA Profiling Tools – Nsight Systems

March 10 NVIDIA Profiling Tools – Nsight Compute

March 25 DAOS: Next-Generation Data Management for Exascale

April/May/June OpenACC Series

May 5-7 2020 ALCF Computational Performance Workshop

2020 Monthly Series CUDA Training Series

2020 Series GPU Hackathon Series  

More Information about Upcoming ECP Training Activities

 

IDEAS ECP Webinar: Testing Strategies when Learning Programming Models and Using High-Performance Libraries

March 18, 2020

URL: https://exascaleproject.org/event/testingstrategies/

The next webinar in the series is titled, Testing: Strategies When Learning Programming Models and Using High-Performance Libraries, and will be presented by Balint Joo (Jefferson Laboratory). The webinar will take place on Wednesday, March 18, 2020 at 1:00 pm ET.

Software testing is an invaluable practice, albeit the level of testing in scientific applications can vary widely, from no testing at all to full continuous integration (as discussed in earlier webinars of the HPC-BP series). In this webinar I will consider a specific case: the use of unit-testing when developing a mini-app as an approach to learn about new programming models such as Kokkos and SYCL, or when using (or contributing to) high-performance libraries. I will illustrate with an example from Lattice QCD, focusing on the integration of the QUDA optimized library with the Chroma application. The webinar will focus on lessons learned and generally applicable strategies.

For more information or to register, please visit the URL above.

OpenMP Hackathon at Georgia Tech

April 20-24, 2020

URL: https://sites.google.com/view/omp-hack-atl/home

The Electrical Engineering and Computer Science Department at Georgia Institute of Technology in conjunction with Oak Ridge National Laboratory (ORNL) is organizing an ECP OpenMP Hackathon on April 20–April 24, 2020. This event is sponsored by the Exascale Computing Project (ECP), and driven by the ECP SOLLVE Project. We encourage participation of teams especially interested in porting and optimizing their applications by using the latest OpenMP features.

For more information or to register, please visit the URL above.

Kokkos Bootcamp and Training

April 21-24, 2020

URL: https://www.olcf.ornl.gov/calendar/kokkos-bootcamp-and-training/

The Oak Ridge Leadership Computing Facility (OLCF) will host a Kokkos training event organized by ECP on April 21-24, 2020. This workshop is intended to teach new Kokkos users how to get started and to help existing Kokkos users to further improve their codes. The training will cover the minimum required topics to get your application started on using Kokkos, and Kokkos experts will be on hand to help the more advanced users. For more information or to register, please visit the URL above.

Other Events that Might be of Interest to ECP Project Teams

 

NVIDIA Profiling Tools – Nsight Systems

March 9, 2020

URL: https://www.olcf.ornl.gov/calendar/nvidia-profiling-tools-nsight-systems/

 

On March 9, 2020, NVIDIA will present a webinar on how to use NVIDIA’s Nsight Systems – a statistical sampling profiler with tracing features – on Summit. Nsight Systems and Nsight Compute are NVIDIA’s next-generation profiling tools for understanding and optimizing the performance of CUDA, OpenACC, or OpenMP applications. NVIDIA recommends transitioning to these new tools since nvprof and Visual profiler will be deprecated in a future CUDA release. The presentation will be delivered remotely, but there will be an in-person viewing of the webinar for participants with current ORNL badges. For more information or to register, please visit the URL above.

 

NVIDIA Profiling Tools – Nsight Compute

March 10, 2020

URL: https://www.olcf.ornl.gov/calendar/nvidia-profiling-tools-nsight-compute/

 

On March 10, 2020, NVIDIA will present a webinar on how to use NVIDIA’s Nsight Compute – a kernel-level analysis and performance metric tool – on Summit. Nsight Systems and Nsight Compute are NVIDIA’s next-generation profiling tools for understanding and optimizing the performance of CUDA, OpenACC, or OpenMP applications. NVIDIA recommends transitioning to these new tools since nvprof and Visual profiler will be deprecated in a future CUDA release. The presentation will be delivered remotely, but there will be an in-person viewing of the webinar for participants with current ORNL badges.

For more information or to register, please visit the URL above.

DAOS: Next Generation Data Management for Exascale

March 25, 2020

URL: https://www.alcf.anl.gov/events/daos-next-generation-data-management-exascale

The Argonne Leadership Computing Facility (ALCF) is presenting the next Aurora Early Adopter Series webinar on March 25, 2020. The Distributed Asynchronous Object Storage (DAOS) is an open-source, scale-out object store designed from the ground up for massively distributed Non-Volatile Memory (NVM). DAOS takes advantage of next-generation NVM technology, like Storage Class Memory (SCM) and NVM express (NVMe), and is extremely lightweight since it operates end-to-end in user space with full OS bypass. DAOS offers a shift away from an I/O model designed for block-based and high-latency storage to one that inherently supports fine-grained data access and unlocks the performance of the next-generation storage technologies. This presentation will introduce the key concepts behind DAOS and the software ecosystem enabling this technology. We will then provide more details on the DAOS deployment on Aurora and how applications will benefit from this new storage tier.

For more information or to register, please visit the URL above.

OpenACC Training Series

April 17, May 28, and June 23

URL: https://www.olcf.ornl.gov/openacc-training-series/

OpenACC is a directive-based approach to parallel programming for heterogeneous architectures, where developers specify regions of code (written in C, C++, and Fortran) to be offloaded from a host CPU to a GPU. This approach is meant to reduce the amount of programming effort required of developers relative to low-level models, such as CUDA.

NVIDIA will present a 3-part OpenACC training series intended to help new and existing GPU programmers learn to use the OpenACC API. Each part will include a 1-hour presentation and example exercises. The exercises are meant to reinforce the material from the presentation and can be completed during a 1-hour hands-on session following each lecture (for in-person participants) or on your own (for remote participants).

For more information or to register, please visit the URL above.

2020 ALCF Computational Performance Workshop

May 5-7, 2020

URL: https://www.alcf.anl.gov/events/2020-alcf-computational-performance-workshop

From May 5–7, 2020, the ALCF will host the annual ALCF Computational Performance Workshop to help researchers achieve computational readiness on ALCF computing resources. Workshop participants will have the opportunity to:

  • Work directly with ALCF and industry professionals during the workshop and dedicated hands-on sessions

  • Explore advanced techniques and tools to enhance code performance and expand your data science skills

  • Benchmark and debug your code with exclusive reservations on ALCF computing systems

  • Prepare for a major allocation award (e.g., INCITE, ALCC, ALCF Data Science Program)

For more information or to register, please visit the URL above.

CUDA Training Series

Monthly in 2020

URL: https://www.olcf.ornl.gov/cuda-training-series/

NVIDIA will present a 9-part CUDA training series intended to help new and existing GPU programmers understand the main concepts of the CUDA platform and its programming model. Each part will include a 1-hour presentation and example exercises. The exercises are meant to reinforce the material from the presentation and can be completed during a 1-hour hands-on session following each lecture (for in-person participants) or on your own (for remote participants).  OLCF and NERSC will both be holding in-person events for each part of the series, where participants can watch the presentations and get help from experts during the hands-on sessions. In-person participants without current Summit or Cori-GPU access will be given temporary accounts to work on the examples.

For more information or to register, please visit the URL above.

2020 GPU Hackathon Series

URL: https://gpuhackathons.org/events

These GPU hackathons are 5-day coding events in which teams of developers prepare their own applications(s) to run on GPUs or focus on optimizing their application(s) that currently run on GPUs. Teams should consist of three or more developers who are intimately familiar with (some part of) their application, and they will work alongside two mentors with GPU programming expertise. If you want/need to get your code running (or optimized) on a GPU-accelerated system, these hackathons offer a unique opportunity to set aside 5 days, surround yourself with experts in the field, and push toward your goals.

TAMIDS Data Science Trainee Program

Posted on by

Overview

Though its Data Science Trainee Program, TAMIDS helps faculty and researchers develop Data Science projects, match interested students to work on them, and provide technical guidance and mentorship during the project.

With the rapid development of information technologies, the applications of data science has dramatically changed various aspects of our society and economy. In responding to this emerging trend,  the Texas A&M Institute of Data Science (TAMIDS) was established to pursue new approaches to data science research, education, operations and partnership at Texas A&M University.

Among all the objectives of TAMIDS, the education of the new generation of researchers that combine their disciplinary competences with data science expertise is of paramount importance. Through collaboration with A&M colleges, research agencies, and industrial partners, the TAMIDS Data Science Trainee Program breaks college boundaries to bring together the expertise and skills from science, engineering, operations, business, health, education, etc. to solve challenging problems while preparing our students for their future career success.

Roles and Registration

We identify three roles – Project Leader, Trainee, and Consultant – in which people can be involved in the program with TAMIDS.

Project Leaders: 

  • Propose Data Science projects by submission here; the proposals are posted online
  • Select and supervise one or more interested trainees to participate in the project
  • Help trainee to acquire domain knowledge needed to conduct the project
  • TAMU Role for Project Leaders: faculty, research staff, post-doc or operations staff

Trainees:

  • Register to participate in the program here and indicate their interest in specific project proposals
  • Participate in proposed project(s)
  • Attend TAMIDS and HPRC training events on Data Science and computing if needed
  • Learn background domain knowledge needed to conduct their project(s)
  • TAMU Role for Trainees: undergraduate or graduate students

Consultants: 

  • Assist Project Leaders with development of project proposals and trainee selection if requested
  • Provide trainee mentorship, project consultancy, and helps with evaluation
  • Consultants can register here
  • TAMU Role for Consultants: faculty, research staff, post-doc, operations staff or graduate students

TAMIDS will support and sustain the Data Science Traineeship Program by (1) managing the program organization; (2) assisting in matching leaders, projects and trainees; (3) organizing Data Science workshops and training programs; (4) helping with project computing and storage resources, and (5) helping develop Data Science courses and curriculum with domain emphases.

We invite A&M faculty, researchers, staff, and students to join this program to promote research, education, service, operations, and outreach in Data Science across Texas A&M. With your involvement and contribution, we will build a vibrant research and education environment for data science at Texas A&M.

Contact Information

For questions about the TAMIDS Data Science Traineeship Program, please contact Dr. Jian Tao, jtao@tamu.edu

TAMIDS Tutorial Workshop Series – Interpretable Machine Learning: Concepts and Techniques

Posted on by

Dr. Xia “Ben” Hu, Assistant Professor and Lynn ’84 & Bill Crane ’83 Faculty Fellow from the Dept. of Computer Science & Engineering, Texas A&M University will lead a tutorial workshop on Interpretable Machine Learning: Concepts and Techniques. The workshop will cover fundamental concepts as well as the state-of-the-art algorithms with implementations in interpretable machine learning.

February 21, 2020

2:00 pm – 5:00 pm

ETB 1005

More information about the workshop can be found at
https://tamids.tamu.edu/2020/02/09/workshop-interpretable-machine-learning/

Workshop background and topics
In many real-world applications, such as Healthcare and Cybersecurity, domain experts would appropriately trust and effectively manage prediction results only if they can understand the prediction model as well as results. For example, it is critical, for not only physicians but also patients, to understand why a patient is diagnosed with pre-diabetes and how the decision is made by a predictive model. This workshop will cover fundamental concepts as well as the state-of-the-art algorithms with implementations in interpretable machine learning. First, we will introduce the background of this problem, and widely used concepts and problem definition of interpretable machine learning. Second, we will discuss the system architecture and main algorithms, as well as our current progress, to bridge the gap between powerful deep learning algorithms and interpretable shallow models through model and application perspectives. At the end, we will introduce XDeep, which is an open-source Python package developed to interpret deep models for both practitioners and researchers. XDeep takes a trained deep neural network (DNN) as the input, and generates relevant interpretations as the output with the post-hoc manner. From the functionality perspective, XDeep integrates a wide range of interpretation algorithms from the state-of-the-arts, covering different types of methodologies, and is capable of providing both local explanation and global explanation for DNN when interpreting model behaviors.

Workshop organization
The first 1.5 hours of the tutorial is an introductory exposition of the topic. The second 1.5 hours is a practical session that helps the audience consolidate their knowledge through hands-on computational experience. Workshop participants should bring their own laptop.

Background knowledge advised for participants
Participants must have at least a basic knowledge of machine learning concepts from supervised and unsupervised learning. Some understanding of deep learning and frameworks (e.g. TensorFlow or PyTorch) would be helpful. Basic experience with Python programming on machine learning problems is assumed.

Workshop attendance and registration
Please register to attend the workshop at https://tinyurl.com/yx7b9u6e. Registration is free but is required due to space limitations.

Biography of the workshop leader
Dr. Xia “Ben” Hu is an Assistant Professor and Lynn ’84 and Bill Crane ’83 Faculty Fellow at Texas A&M University in the Department of Computer Science and Engineering. Hu directs the Data Analytics at Texas A&M (DATA) Lab. Dr. Hu has published over 100 papers in several major academic venues, including KDD, WWW, SIGIR, IJCAI, AAAI, etc. An open-source package developed by his group, namely AutoKeras, has become the most used automated deep learning system on Github (with over 6,000 stars and 1,000 forks). Also, his work on deep collaborative filtering, anomaly detection and knowledge graph have been included in the TensorFlow package, Apple production system and Bing production system, respectively. His papers have received several awards, including WWW 2019 Best Paper Shortlist, INFORMS 2019 Best Poster Award, INFORMS QSR 2019 Best Student Paper Finalist, IISE QCRE 2019 Best Student Paper Award, WSDM 2013 Best Paper Shortlist, IJCAI 2017 BOOM workshop Best Paper Award. He is the recipient of JP Morgan AI Faculty Award, Adobe Data Science Award, NSF CAREER Award, and ASU President Award for Innovation. His work has been featured in several news media, including the MIT Technology Review, ACM TechNews, New Scientist, Defense One, and others. Hu’s work has been cited more than 6,000 times with an h-index of 36. He was the conference General Co-Chair for WSDM 2020. More information can be found at http://faculty.cs.tamu.edu/xiahu/.

Further information
For more information about TAMIDS tutorial workshop series, please contact Ms. Jennifer South at jsouth@tamu.edu

NVIDIA DLI Deep Learning for Computer Vision Workshop (Saturday, Feb 1, 2020)

Posted on by

The NVIDIA Deep Learning Institute (DLI), the Texas A&M Institute of Data Science, the Texas A&M High Performance Research Computing, and the Texas Engineering Experiment Station invite you to attend a hands-on deep learning workshop on Feb 1st, 2020 from 8:30AM to 5:00PM at the ILSB Auditorium exclusively for verifiable academic students, staff, and researchers. NVIDIA DLI offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing.

Bring-Your-Own-Data (BYOD) Workshops – 2020

Posted on by

The Texas A&M Institute of Data Science (TAMIDS), Texas A&M High Performance Research Computing (HPRC), and Texas Engineering Experiment Station invite you to join our Bring-Your-Own-Data (BYOD) workshop! The primary goal of this workshop is to help Aggie researchers take advantage of the latest data analytics technologies and Texas A&M high performance computing facilities to speed up various data science projects. This is a FREE service offered to all researchers at Texas A&M.

Time: Jan 21 – Apr 14, 2020 Tuesdays.
Location: 235-I Wisenbaker Engineering Building, 188 Bizzell St, College Station, Texas 77843

Please note that this is NOT a training session, but more in forms of a code development working meeting focusing exclusively on your project with a goal to overcome techinical hurdles you may have to move forward with your data science projects. Given the limited time and resources available to offer this workshop, you must be prepared with a determined mind to create substantial progress. We can only work on the software applications that you write and plan to maintain yourself or the applications that are built on top of an open source platform.

You are advised to bring your own laptop, but it is not required as long as you provide means to share your data with us at the workshop. Please feel free to contact the organizers if you have any questions or comments.

More about the BYOD workshop can be found here.

TAMIDS Data Science Webinar Series

Posted on by

The Texas A&M Institute of Data Science invites you to attend the TAMIDS Data Science Webinars from Oct 15 to Oct 29, 2019. This webinar series is to introduce the fundamentals of data science (with python) to students and researchers from the Texas A&M University system.

Registration: FREE

More information of the webinars can be found at

https://tinyurl.com/yyxwbzy6