Job Opening: Modeling, Simulation and Optimization of Energy Systems Research Engineer

By | Feature, SC2 jobs

The Bosch Research and Technology Center in Sunnyvale, CA seeks to hire an outstanding research engineer to develop novel hybrid multiscale, cross-domain modeling, simulation, and optimization tools for Bosch products. This engineer would join a team of PhDs with a variety of competences including high fidelity CFD-based multiphysics modeling, adjoint-based optimization, high performance computing and model-based state estimation and controls. The team focuses on design and optimization of residential and transportation technology targeting high energy efficiency and reduced emissions, including fuel cells, electric vehicle components, and heating systems.

Read more.

miRcore is looking for group leaders to guide high school students in performing computational biomedical research

By | Feature, SC2 jobs

miRcore, a 501(c)(3) non-profit org., is looking for group leaders to guide groups of high school students in performing computational biomedical research. Group leaders will be paired with a younger co-lead. During our remote camps, students will finish a research project within about one week, while learning and applying new tools every day. Group leaders will be expected to assist and support these students.

2017 miRcore GIDAS Biotechnology Summer Camp participants

Ideal group leaders are:
1) Graduate or college students (professionals with PhDs welcome)
2) Experienced (or interested) in computational biomedical research
3) Have a passion to inspire young minds
4) Able to commit to a specific camp

Camps run June-August, and leaders will be compensated with $450 per camp session.
Group leaders usually describe the experience as fun, meaningful, an opportunity to learn new research skills, and reigniting their passion for science.

Learn more and apply here: https://forms.gle/6oD9cDqULebxarCE7

The crucial role of massively parallel simulations in future space exploration missions

By | HPC, News, Research

The NASA Mars 2020 Mission was launched with the goal of seeking signs of ancient life and collecting samples of rock and regolith (broken rock and soil) for possible return to Earth. Perseverance, the mission’s rover, is testing technologies to help pave the way for future human exploration of Mars. While Perseverance was launched in the summer of 2020, landing on the martian surface on February 18, 2021, the journey started years earlier when the mission’s objectives were outlined, including realistic surface operations, a proof-of-concept instrument suite, and suggestions for threshold science measurements that would meet the proposed objectives. The success of this, as well as past and future missions, is the collective result of thousands of NASA funded projects from teams of researchers and scientists from all over the country that span many decades. University of Michigan Professor Jesse Capecelatro (Mechanical Engineering & Aerospace Engineering) is the lead of one of these projects. In 2016, his research group started working on a project aimed to develop high fidelity models of plume-Induced soil erosion during lunar and planetary landings that will be used in future missions. 

During descent, exhaust plumes fluidize surface soil and dust, forming craters and buffeting the lander with coarse, abrasive particles. The SkyCrane technology, used by the Curiosity Rover in 2012 and by Perseverance in 2021, was designed to avoid plume-surface interactions by keeping the jets far above the surface. Regardless of this feature, a wind sensor on NASA’s Mars Curiosity rover was damaged during landing. In the Perseverance’s video footage of the landing, significant erosion and high-speed ejecta were observed.  It is also not a practical option for future crewed and sample return missions. 

NASA is aiming to improve rovers’ landing gears for future missions. Computational models and simulations are a critical component to achieve this as it is not feasible to mimic the martian or other celestial bodies entry conditions and run thousands of tests in a lab anywhere on Earth. This is where Prof. Capecelatro’s research group, including doctoral candidates Greg Shallcross, and Meet Patel, and postdoctoral fellow Medhi Khalloufi, work comes in as the accurate prediction of surface-plume interactions is necessary for the overall success of future space missions. While simulations of surface-plume interactions have been conducted in the past, these are outdated, and typically relied on simplified assumptions that prevent a detailed and dynamic analysis of the fluid-particle coupling. Capecelatro’s research code will provide NASA with a framework to better predict how different rover designs would impact the landing, specifically the effects of the force of the collision on the planet’s surface, and ability to adjust the rover’s landing trajectory independent of the NASA mission control team on earth.  

Prof. Capecelatro’s research project utilizes predictive simulation tools to capture the complex multiphase dynamics associated with rocket exhaust impingement during touchdown. Even in the most powerful supercomputers, a direct solution approach is only capable of accounting for  about a thousand particles at the same time, so accurate and predictive multi-scale models of the unresolved flow physics are essential. 

Full landing site image credit: NASA/JPL-Caltech (mars.nasa.gov/resources/24762/mars-sample-return-lander-touchdown-artists-concept/); particle and intermediate scale images: Capecelatro’s Research Group

Particle Scale

The group has been developing the simulation capabilities to directly resolve the flow at the sub-particle scale to shed light on important physics under the extreme conditions relevant to particle-structure interactions. Their model uses a massively parallel compressible particle-laden flow simulation tool where the exhaust plume and its corresponding flow features are computed in an Eulerian-Lagrangian framework. At this scale, for example, the flow between individual particles are resolved, providing important insight on drag and turbulence under these extreme conditions.

Intermediate Scale

As a next step, the particle-scale results inform models used in the intermediate-scale simulations developed by the group, where particles are still tracked individually but the flow is not resolved at a sub-particle resolution, allowing them to simulate upwards of 1 billion particles. At this scale, an Eularian-Lagrangian framework is used to incorporate the ground’s particle flow with the jet’s plume. 

Full Landing Site Scale

While the intermediate-scale simulations allow to study erosion and cratering, a full landing site that contains trillions of particles is still out of reach even in the most powerful HPC clusters. After further modeling, Capecelatro’s multi-scale framework will be handed over to NASA where it will be incorporated in simulations of the full landing site. At this scale, NASA’s framework uses an Eularian-based, two fluid model that treats both fluid and particles as a continuum, informed by the particle- and middle-scales models. 

Mission Mars 2020 is expanding NASA’s robotic presence on the red planet. While it is a big step to set the stage for future human exploration, the Perseverance Rover needs further redesign to make the voyage safe for humans. Capecelatro’s physics-based models are aiding this task by helping predict and model more accurately the outcomes of a spacecraft attempting to safely land millions of miles from home. As in many other fields, computational science will continue to play a critical role in the future of humanity’s quest to conquer space. #computationalscience everywhere!

Related links:
Sticking the landing on Mars: High-powered computing aims to reduce guesswork
Capecelatro’s Research Group
NASA 2020 Mars Mission: Perseverance Rover

Summer STEM Institute (SSI) Teaching Opportunties

By | News, SC2 jobs

The Summer STEM Institute (SSI) is a virtual education program that teaches programming, data science, and research.

 

SSI is currently hiring for both part-time and full-time roles for summer 2021. Both roles offer competitive compensation.

Role 1: Part-Time Research Mentor (10-15 hours/week):

Responsibilities: Lead a virtual lab of 2-3 students; mentor students through the ideation and completion of their own computational or theoretical research projects; support students through the creation of weekly research deliverables, including a background research report, a research proposal, and a final paper and presentation

Qualifications: Passion for teaching and mentorship; graduate student, postdoctoral fellow, or (in exceptional circumstances) undergraduate with extensive programming or research experience in a computational or theoretical field; past research experiences and deliverables, including published papers and presentations

Note: Research mentors are able to work for the program alongside full- time job, internship, or research commitments.

Role 2: Full-Time Teaching Fellow (40 hours/week):

Responsibilities: Teach and work closely to support students through the data science and research bootcamp, answer student questions and discussion board posts; host office hours; leave feedback on student homework assignments

Qualifications: Passion for teaching and mentorship; experience with Python programming and data science libraries (numpy, pandas, matplotlib, sklearn); experience with data science and the research process


Interested undergraduate and graduate students are encouraged to apply. Please fill out this 2-minute interest form. If we decide to move forward with your application, we will send more information about the roles and also times to schedule an interview. If you have any questions, please reach out to hiring@summersteminstitute.org.

Seeking Master’s Student Research Engineer to Build GUI for IGA Meshing

By | News, SC2 jobs

YB Numerics Inc. is seeking to hire a research engineer to work on the development of a meshing tool and GUI to support general-purpose volumetric mesh generation for Isogeometric Analysis (IGA).

 

IGA is a novel computational modeling approach that makes use of smooth spline functions commonly employed in Computer-Aided Design and Computer Graphics to carry out Finite Element Analysis in solid and fluid mechanics, coupled fluid-structure interaction (FSI), and other areas.

 

The ideal candidate would be someone pursuing their MS degree in Computational Science and Engineering or Computer Science. The engagement can be from 20 hours/week all the way to full-time employment. The candidate may work remotely, relocation to the Providence area is not required. The candidate may also use some products of this work to contribute to his/her MS thesis if desired.

 

Duties:
The research engineer will mainly work on the implementation of a GUI for generating volume meshes for IGA using the multiblock Non-Uniform Rational B-Spline (NURBS) technology. The research engineer will also help generate NURBS meshes and carry out computational analyses of solid and fluid mechanics applications using the meshes produced by the meshing tool. The research engineer will interact with the YB Numerics and Rice University team members and their collaborators on the GUI development, NURBS meshing, and numerical simulations.

 

Required Qualifications:
– Bachelor’s degree in Computer Science or Mechanical, Civil or Aerospace (or related)
Engineering
– Experience with Qt GUI programming (Qt OpenGL and WebGL)
– Experience with team programming environments (GitHub/GitLab, CMake, Docker)
– Must be a US Citizen or Permanent Resident

 

Desired Qualifications:
– Master’s degree
– Good knowledge of geometric modeling
– Good knowledge of numerical methods
– Knowledge of fluid and solid mechanics
– Experience with Fortran 90 programming
– Experience with high-performance computing (MPI, OpenMP)


Interested candidates should send an e-mail to ybnumerics@gmail.com with the
subject line “Interested in IGA Meshing Tool and GUI Development”.

Argonne Training Program on Extreme-Scale Computing

By | News, SC2 jobs

The annual Argonne Training Program on Extreme-Scale Computing (ATPESC) is set to take place August 1–13, 2021. The call for applications is now open through March 1, 2021.

 

Apply now for an opportunity to learn the tools and techniques needed to carry out scientific computing research on the world’s most powerful supercomputers. ATPESC participants will be granted access to DOE’s leadership-class systems at the ALCF, OLCF, and NERSC.

The Argonne Training Program on Extreme-Scale Computing (ATPESC) provides intensive, two-week 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.

The core of the program will focus on programming methodologies that are effective across a variety of supercomputers and that are expected to be applicable to exascale systems. Additional topics to be covered include computer architectures, mathematical models and numerical algorithms, approaches to building community codes for HPC systems, and methodologies and tools relevant for Big Data applications.

PROGRAM CURRICULUM

Renowned scientists and leading HPC experts will serve as lecturers and guide the hands-on sessions. The core curriculum will cover:

  • Hardware architectures
  • Programming models and languages
  • Data-intensive computing and I/O
  • Visualization and data analysis
  • Numerical algorithms and software for extreme-scale science Performance tools and debuggers
  • Software productivity
  • Machine learning and deep learning tools and methods for science

ELIGIBILITY AND APPLICATION

Doctoral students, postdocs, and computational scientists interested in attending ATPESC can review eligibility and application details on the website.

There are no fees to participate in ATPESC. Domestic airfare, meals, and lodging are also provided. Application deadline: March 1, 2021.

Doctoral students, postdocs, and computational scientists interested in attending ATPESC can review eligibility and application details on the application instructions web page.

The event will be held in the Chicago area. If an in-person meeting is not possible, it will be held as a virtual event.

Note: There are no fees to participate. Domestic airfare, meals, and lodging are provided.

IMPORTANT DATES – ATPESC 2021

  • March 1, 2021 – Deadline to submit applications
  • April 26, 2021 – Notification of acceptance
  • May 3, 2021 – Account application deadline

For more information, contact support@extremecomputingtraining.anl.gov

Across six continents, scientists use computation to optimize cities’ responses to hazardous events

By | Events, Research, Uncategorized

“Community resilience is a manifestation of the human trait of adaptation. A resilient community is able to withstand and recover from hazardous events with minimal disruption to its way of life.”

Sherif El-Tawil
Antoine E. Naaman Collegiate Professor,
Department of Civil and Environmental Engineering

The combination of natural hazards, climate change, and the COVID-19 pandemic has demonstrated the importance of community resilience. Community resilience is a manifestation of the human trait of adaptation. A resilient community is able to withstand and recover from hazardous events with minimal disruption to its way of life. As humans, we seek to use our ability to engineer to adapt to the threat of natural hazards. Although achieving resilience is technically challenging and expensive, communities must strive to accomplish the highest level of resilience attainable with the engineering and financial resources available.

The science behind resilience engineering involves many disciplines, each dedicated to a subset of the overall problem. Complex issues lie at the intersection of these subsets, but interdisciplinary research is difficult to achieve because researchers in various disciplines frame problems and perform research from different perspectives and along distinct pathways. However, as computational models are well established in each discipline, computation is a natural language that links the disciplines together.

Last fall, the Michigan Institute for Computational Discovery and Engineering and the department of Civil and Environmental Engineering brought together established leaders and some of the most innovative rising scholars in the computational hazards research, to present and discuss different computational approaches used in modeling, assessing, and defining standards for community resilience. The speakers included representatives from leading research centers in the field: keynote speaker, Terri McAllister, from the National Institute of Standards and Technology (NIST); John van de Lindt (Colorado State University) co-director of the NIST-funded Center of Excellence (CoE) for Risk-Based Community Resilience Planning; Gregory Deierlein (Stanford University) from the SimCenter, which represents a consortium of universities on the U.S. West Coast; Sherif El-Tawil (University of Michigan) from ICoR, and Wael El-Dakhakhni (McMaster University) from INTERFACE.  They were joined

by other leaders in the fields including Tasos Sextos from Bristol University, UK, Xinzheng Lu, head of the Institute of Disaster Prevention and Mitigation of Tsinghua University; Hiba Baroud from Vanderbilt University, and Seth Guikema from the University of Michigan. The speakers highlighted their Centers’ or research groups’ capabilities and contributions, then reconvened for a panel discussion to address questions from the audience of nearly 250 participants from 30 countries, across six continents. The event also included a hands-on workshop that highlighted the Simple Run-Time Infrastructure software toolkit (SRTI). The SRTI is a free, open-source solution developed at the University of Michigan. It enables researchers to connect computer programs and simulators written in different languages, share data during execution, and design hybrid systems using disparate simulator modules, with a primary goal of being user friendly. The applications within this workshop demonstrated how one tool can be used to bring together multiple computational dialects to create a single language in the context of natural hazards research. The SRTI software toolkit is a result of the work of Dr. Sherif El-Tawil’s research group at the University of Michigan, supported by the National Science Foundation’s Office of Advanced Cyberinfrastructure (OAC) under grant CRISP TYPE II – 1638186. (icor.engin.umich.edu).

The range of techniques and principles that were detailed at this workshop can be applied to the current COVID-19 crisis. The pandemic is a perfect example that demonstrates that investing in mitigating risk reduces the cost, both human and material, of a hazard, and that even hazards with such a low probability of occurrence require enough investment to make ourselves resilient to it. The pandemic also illustrates that computational hazards research is a rich field with many opportunities at the intersection of the various disciplines. One of the most interesting ideas there is to explore is how to fuse sensor data – from the field – with simulations data, to achieve models that can help predict in real time the effect of a natural hazard.

Link to event information and recordings

University of Michigan’s Ph.D. in Scientific Computing: A history of supporting research through education

By | Educational, Feature

#Computationalscience everywhere!

Left side, 2167 configuration console for the IBM/System 360 Model 67-2 (duplex) at the University of Michigan, c. 1969 [Picture by Scott Gerstenberger – Scott Gerstenberger, Public Domain]

The University of Michigan’s joint Ph.D. program in Scientific Computing recently achieved a record enrollment of 137 students. Between 2015, when 15 students were enrolled -mainly from the Colleges of Engineering and Literature, Science and the Arts- and today, the program has witnessed an explosive growth of interest on the part of U-M students. The program now has students enrolled from over 30 departments spanning 8 different schools and colleges, and more than 130 students have graduated in the last 31 years, including 17 students to-date in 2020.

This popularity is emblematic of the dominant role that computation plays in the world today. With the breakneck pace at which new hardware and software architectures are being developed, the boom in simulation-based research in a growing number of disciplines, and the initiatives in data and computational sciences implemented at U-M in the last few years, including the establishment of the Michigan Institute for Computational Discovery & Engineering, and the Michigan Institute for Data Science (MIDAS), it may seem only natural that scientific computing should attract this level of interest. However, like all exceptionally successful undertakings, it owes a great deal to its past. We reached back more than three decades to piece together the history of the Ph.D. in Scientific Computing at U-M.

The broader history of computational science and high performance computing at the University of Michigan is rich and extensive. U-M has been at the forefront of Cyberinfrastructure research for many decades, marked by the acquisition of U-M’s first virtual memory computer in 1967, an IBM 360/67, one of the first computers of its kind in the world. This milestone was followed by many others, including further hardware acquisitions and establishment of new units to support advanced research computing. An important early step was taken in 1985 when the College of Engineering established the Laboratory for Scientific Computation (LaSC). LaSC’s goal was to foster and promote the use of scientific computation in research and instruction at U-M. During those years, several reports from national study committees established computational science as the third pillar of scientific methodology, along with theory and experimentation. Faculty members of LaSC, who were at the forefront of driving these trends  recognized that any initiative in this field needed to include a robust student training program. 

left: Prof. Kenneth Powell (Aerospace Engineering), director of the Ph.D. in Scientific Computing program since 2005; right: Prof. William Martin (Nuclear Eng. and Rad. Sciences), director of the program from 1989 to 2004.

Prominent at that time in LaSC were Prof. William “Bill” Martin (Nuclear Engineering and Radiological Sciences – NERS), the laboratory’s director, Prof. John Boyd (Atmospheric, Oceanic and Space Sciences), the laboratory’s associate director, and Prof. Edward Larsen (NERS), who was hired as part of the College of Engineering’s initiative to move aggressively in the area of scientific computing. Together, they designed a graduate academic program with the goal of giving students a more comprehensive training in numerical analysis and computer science than is typically possible within standard disciplinary programs housed within individual departments and schools. The fundamental idea was that, to excel in computational science and engineering, one must have a thorough understanding of the mathematical and physical problems to be solved, expertise in  the methodologies and algorithms, and a foundation in computer science to be able to apply this arsenal of techniques on modern computer platforms. The need for a thorough understanding of the physical problems led directly to the requirement that students had to be enrolled in a traditional Rackham degree program (i.e., a home department), while the need for mathematical underpinning and knowledge of algorithms and computer science topics led to the requirements for courses in numerical analysis, parallel algorithms, and related topics. The PhD in Scientific Computing program was approved by the State of Michigan in 1988, and enrolled its first students in 1989. This was well in advance of a wider recognition of the centrality of computation in academia and industry. It is true today, as it was in 1988, that students can apply to the PhD in Scientific Computing program from any Rackham-recognized PhD program at the UM. This unique and flexible administrative structure has enabled the rapid growth experienced in recent years as scientific computing has become an indispensable tool in many fields of academic endeavor. 

Prof. Quentin Stout, director of the Center for Parallel Computing 1992-2001 [Picture source: NASA Insights 1998]

The oversight of the degree program has evolved over the years as administrative structures around scientific computing have shifted. Regardless of its administrative home, the program has always been organized under the Rackham School of Graduate Studies. Originally, the College of Engineering had oversight of the program, with Prof. Martin appointed as director, and with guidance from the LaSC Education Committee. This setup continued through the merger of LaSC and the Center for Parallel Computing1 into the Center for Advanced Computing in 2001. In 2005, Prof. Kenneth Powell (Aerospace Engineering) was named director of the program succeeding Prof. Martin, and has continued in the role since. In 2008, the Office of Research Cyberinfrastructure (ORCI) was established, and the oversight of the program changed to the U-M Office of Research. In 2013, when ORCI was re-named as Advanced Research Computing, and the Michigan Institute for Computational Discovery & Engineering (MICDE) was born, oversight was transferred to MICDE.

Since its inception, the program has been described as intended for students who will make intensive use of large-scale computation, computational methods or algorithms in their doctoral studies. Although the requirements and goals of the program have not  changed in 31 years, the research applications, the algorithms and methodologies, and the computer platforms have been in constant evolution. Naturally, the courses offered in support of the program have followed closely. In 1989 the core research areas behind the program were computational fluid dynamics, advanced computer architectures, and particle transport, with the majority of the students coming from engineering, and mathematics. Still, students working in areas where computation was less recognized, such as AIDS transmission or social research projects, also were enrolled. Over the next two decades, the tremendous increase in simulation-based research by the faculty in engineering and physical sciences added many other focus areas, including material science, astronomy, and high energy physics, to name just a few. This growth added a new driver as data-intensive research gained importance in those fields. 

Prof. Suzanne Weekes, Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute (U-M 1995, Mathematics and Scientific Computing) [Picture source: SIAM News Sept. 2020]

Several faculty members have had an important role shaping the program, by offering fundamental courses and providing mentorship. Notably, Prof. Quentin Stout, from Computer Science and Engineering, has had a prominent role in the program. He was the founding director of the Center for Parallel Computing, which  provided the basis for subsequent units in this sphere at U-M. He also developed, and has been teaching, Parallel Computing since 1985, innovating its curriculum to remain at the cutting edge of the current techniques, important aspects of which have been based on his own research. Other foundational courses, such as the Department of Mathematics’ Numerical Methods for Scientific Computing I & II and Numerical Linear Algebra have been offered for more than 30 years. More recently the Department of Physics course, Computational Physics, and the College of Engineering course, Methods and Practice of Scientific Computing, along with an array of courses in machine learning, have played prominent roles in transforming the curriculum in scientific computing as research in these areas has likewise redefined the field.

Unsurprisingly, the Ph.D. in Scientific Computing has produced many exceptional alumni. The first student graduated from the program in 1992, and notably for its time, two of the first four graduates were women, when gender imbalance was barely recognized. A majority of the program graduates went on to  positions in academia or the National Laboratories, with the rest working in varied fields in industry or government. Some of these outstanding alumni include Suzanne Weekes, U-M 1995 (Mathematics and Scientific Computing), currently Associate Dean of Undergraduate Studies, ad interim, and Professor of Mathematical Sciences at Worcester Polytechnic Institute. Prof. Weekes has recently been named SIAM executive director, and will start her new role on January 1, 2021.  Another alumna, Rona Oran, U-M 2014 (Space Science and Scientific Computing), is a computational plasma physicist at MIT and a member of the NASA team that is designing and planning a mission to the metal asteroid Psyche to be launched in 2020.

The current goal of the program is still founded on the original idea of strengthening the students’ foundations in methodology and computer science. The leadership of the program strives to bring computational science to more research fields, but importantly, aims to do so by enhancing diversity in the field. An important marker of U-M’s success on this front came in  2018 in the form of the Henry Luce Foundation’s award to the University of two Claire Boothe Luce Ph.D. fellowships for women to enroll in the Ph.D. in Scientific Computing. The program is committed to pursuing other such opportunities and creating an environment where students of all backgrounds and identities feel welcome and thrive.

1 In 1992 U-M was awarded a major equipment grant by the National Science Foundation to create a testbed of parallel computing architectures. The Center for Parallel Computing was established to operate the facility. The center installed and operated several different parallel computers over the years, including KSR-1, KSR-2, Convex Exemplar, SGI PowerChallenge, IBM SP2, and AMD and Apple clusters.

Los Alamos National Laboratory, Multiple HPC Intern Summer Opportunities

By | News, SC2 jobs

For questions about internships and instructions on how to apply, please email HPCRecruits@lanl.gov


HPC Data Movement and Storage Team: Upcoming Student Project Opportunities

PROJECT: EMERGING STORAGE SYSTEM(S) EVALUATION

(Lead Mentor: Dominic Manno)

Storage systems are evolving as technology, such as flash, becomes economically viable. Vendors implementing cutting edge hardware solutions often approach LANL to help gain insight into how these systems could move into the real world (HPC applications). Work in this area includes potential modifications to filesystems, filesystem configuration/tuning, testing hardware, fixing bugs, finding bottlenecks anywhere in the stack in order to increase efficiency and make the storage system faster.

Preferred skills:

● Interest in HPC and storage systems
● Comfortable with computer hardware
● Strong analytical skills
● Benchmarking experience
● Experience with linux and scripting (bash, csh, Python, etc.)
● Comfortable with C programming

PROJECT: FILE SYSTEM(S) FEATURE AND TOOLSET EVALUATIONS

(Lead Mentor: Dominic Manno)

File systems evolve along with user requirements. New features are implemented to accommodate changing workloads and technology. LANL’s storage team must evaluate new features and their impact on HPC applications. This work will explore file system features, modifications to current build procedures/processes, and impact to LANL’s storage team metric collection tooling. Work in this area includes building source code (kernel included), configuring linux servers, configuring a basic distributed file system, benchmarking, experiment design, analysis of data, and scripting.

Preferred skills:

● Knowledge of and interest in filesystems
● Experience with Linux and Command Line Interface
● Experience with code build systems and software
● Interest in HPC and storage systems at scale
● Benchmarking experience

ABOUT THE HPC DATA MOVEMENT AND STORAGE TEAM:
The High Performance Computing (HPC) Data Storage Team provides vanguard production support, research, and development for existing and future systems that feed and unleash the power of the supercomputer. The Data Storage Team designs, builds and maintains some of the largest, fastest and most complex data movement and storage systems in the world, including systems supporting 100 Petabytes of capacity. We provide storage systems spanning the full range of tiers from the most resilient archival systems to the pinnacle of high-speed storage, including all-flash file systems and systems supplying bandwidth that exceeds a terabyte per second to some of the largest and fastest supercomputers in the world. Innovators and builders at heart, the Data Storage team seeks highly motivated, productive, inquisitive, and multi-talented candidates who are equally comfortable working independently as well as part of a team. Team member duties include: designing, building, and maintaining world-class data movement and storage systems; evaluating and testing new technology and solutions; system administration of HPC storage infrastructure in support of compute clusters; diagnosing, solving, and implementing solutions for various system operational problems; tuning file systems to increase performance and reliability of services; process automation.


HPC Platforms Team: Upcoming Student Project Opportunities

PROJECT: HPC CLUSTER REGRESSION
(Lead Mentor: Alden Stradling)

Building on work done by our interns this summer, we are continuing the process of adapting existing regression testing software to do system-level regression testing. Using the LANL- developed Pavilion2 framework in combination with Node Health Check (NHC) for more detailed information, our interns are moving the system from proof-of-concept in a virtualized test cluster to production-style systems to measure effectiveness and system performance impact, and to flesh it out as a running system. Also on the agenda is to make test creation and propagation simple, allowing regression detection to be added at the same time as fixes are made to the system.

Preferred skills

• Interest in HPC and modern infrastructure management at scale
• Problem solving and creativity
• Configuration Management
• Version Control
• Programming experience in bash, python or perl
• Strong background in UNIX and familiarity using CLI

About the HPC Platforms Team
The High Performance Computing (HPC) Platforms Team provides vanguard system and runtime support for some of the largest and fastest supercomputers in the world, including multi-petaop systems (e.g., the recently deployed 40 Peta operations per second Trinity Supercomputer). Troubleshooters and problem- solvers at heart, the HPC Platforms Team seeks highly motivated, productive, inquisitive, and multi-talented candidates who are equally comfortable working independently as well as part of a team. Team member duties include: system deployment, configuration, and full system administration of LANL’s world-class compute clusters; evaluating and testing new technology and solutions; diagnosing, solving, and implementing solutions for various system operational problems; system administration of HPC network infrastructure in support of compute clusters; diagnosing, solving, and implementing solutions for various system operational problems; system software management and maintenance, including security posture maintenance; tuning operating systems to increase performance and reliability of services; developing tools to support automation, optimization and monitoring efforts; interacting with vendors; and communicating and collaborating with other groups, teams, projects and sites.


HPC Design Group: Upcoming Student Project Opportunities

PROJECT: OPTIMIZING “SPACK CONTANERIZE” FOR USE WITH CHARLIECLOUD

(Lead Mentor: Tim Randles)

The Spack software package manager has the ability to output software build recipes as dockerfiles. These dockerfiles often require hand-editing to work well with Charliecloud. In this project you will work with the Charliecloud team at Los Alamos to identify common problems with Spack dockerfiles. You will then determine if these problems are best addressed by making changes to Charliecloud’s dockerfile support or if there are improvements that should be proposed to Spack’s containerize functionality. The intern will be expected to implement suggested changes. At the end of the summer the intern will present their work.

PROJECT: BUILDING A GITLAB TEST INFRASTRUCTURE USING THE ANSIBLE REPOSITORY

(Lead Mentor: Cory Lueninghoener)

Use Gitlab’s CI/CD pipeline and runner functionality to build an automated test infrastructure for checkins to our Git-backed Ansible repository. This would start out with getting familiar with Gitlab’s automated pipeline capabilities and running tasks on code checkin, and move on to simple linting tests that run each time a change is checked in. From there, it could move on to running larger test suites on VMs or in containers, all the way up to building and testing virtual clusters and tagging good cluster image releases.

About the HPC DES Group:
The High Performance Computing Design Group focuses on future technologies and systems related to HPC while providing technical resources when needed to the more production focused HPC Groups. Areas of focus include I/O and storage, future HPC architectures, system management, hardware accelerators, and reliability and resiliency. Production timescales of projects vary from weeks in the future for production deployments to 10 years or more for some of the reliability and future architecture work.


Where You Will Work:
Our diverse workforce enjoys a collegial work environment focused on creative problem solving, where everyone’s opinions and ideas are valued. We are committed to work-life balance, as well as both personal and professional growth. We consider our creative and dedicated scientific professionals to be our greatest assets, and we take pride in cultivating their talents, supporting their efforts, and enabling their successes. We provide mentoring to help new staff build a solid technical and professional foundation, and to smoothly integrate into the culture of LANL.

Los Alamos, New Mexico enjoys excellent weather, clean air, and outstanding public schools. This is a safe, low-crime, family-oriented community with frequent concerts and events as well as quick travel to many top ski resorts, scenic hiking & biking trails, and mountain climbing. The short drive to work includes stunning views of rugged canyons and mesas as well as the Sangre de Cristo mountains. Many employees choose to live in the nearby state capital, Santa Fe, which is known for world-class restaurants, art galleries, and opera.

About LANL:
Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

The High Performance Computing (HPC) Division provides production high performance computing systems services to the Laboratory. HPC Division serves all Laboratory programs requiring a world-class high-performance computing capability to enable solutions to complex problems of strategic national interest. Our work starts with the early phases of acquisition, development, and production readiness of HPC platforms, and continues through the maintenance and operation of these systems and the facilities in which they are housed. HPC Division also manages the network, parallel file systems, storage, and visualization infrastructure associated with the HPC platforms. The Division directly supports the Laboratory’s HPC user base and aids, at multiple levels, in the effective use of HPC resources to generate science. Additionally, we engage in research activities that we deem important to our mission.

Los Alamos National Laboratory, Supercomputer Institute Summer Internship Opportunity

By | News, SC2 jobs

PROGRAM OVERVIEW
The Supercomputer Institute is an intense, paid, 11-week, hands-on technical internship for people of all majors interested in the growing field of high-performance computing. You will obtain a thorough introduction to the techniques and practices of HPC; no HPS experience is required.

The program begins with two weeks of “boot camp”. Small teams of interns build, configure, test, and operate an HPC compute cluster starting from scratch, turning a head of equipment, cables, and electricity into a working mini-supercomputer that can run real HPC applications.

Next, the project phase begins. Teams of interns work under the guidance of HPC Division staff mentors on applied research and development projects that address real challenges currently faced by the division. Some projects use the mini-supercomputers built during boot camp, and others use existing LANL resources. These projects regularly influence the division as well as the field of high-performance computing.

Finally, teams present their accomplishments as a poster and technical talk to Laboratory management, staff, and fellow interns in an end-of-summer celebration of intern work.

The program runs June 1, 2021 – August 13, 2021.

View full job post here.

PROFESSIONAL DEVELOPMENT:
In addition to the technical portion of the program, interns also participate in fast-paced, focused professional development work, including:

  • Intense mentoring
  • Teamwork and professional collaboration
  • Resume writing and evaluation
  • Technical poster/presentation design and public speaking
  • Technical seminars on current HPC topics. Past seminars include high-speed networking, Linux containers,
  • parallel filesystems, facilities, and more.
  • Science lectures given by staff from across the Laboratory, from how the Mars Rover works to machine learning/ AI to black hole collisions.
  • Opportunities to sign up for tours of our world-class facilities, including the magnet lab, particle accelerator, million-core supercomputer, and ultra-cold quantum computer.

WHO IS ELIGIBLE TO APPLY:
The program is targeted to rising juniors or seniors, master’s students, and recent graduates with a bachelor’s or associate’s degree. Very highly qualified rising sophomores have been successful in the past, as well as occasional master’s graduates and Ph.D. students who can make a good case that they need hands-on practical training, rather than a research internship.

REQUIRED QUALIFICATIONS:
Interns must meet the following minimum requirements. If you are unsure whether you meet them, please ask us! We don’t want miss someone because they meet requirements in a way we did not anticipate.

  • Computer science, computer engineering, IT, or related experience/training.
  • Intermediate understanding of the Linux OS. For example, this might mean you have basic understanding of how an operating system works, some experience using Linux, and some knowledge of how Linux differs from desktop (e.g., Mac, Window) or phone OSes (Android, iOS).
  • Intermediate command line skills. You should have basic knowledge of the terminal using a shell such as tcsh or Bash. This doesn’t necessarily have to be on Linux (Macs also have a nice command line).
  • Scripting or programming experience of some kind.
  • Collegial, personable, plays well with others; the program is a team sport. Please note this does not mean you have to be “normal”; neurodiversity is encouraged.
  • Well-rounded and curious.
  • Can deal with reasonable deadlines. It’s a fast-paced program, but not high pressure.
  • Meets LANL undergraduate or graduate student program requirements, as applicable.

DESIRED QUALIFICATIONS:
In addition to the above, we’re looking for interns that also have some of the following skills. Note that few interns have all of them.

  • Strong communication skills (written and/or oral).
  • Interesting experience with Linux, hardware, networking, security, filesystems, etc.
  • HPC experience, whether sysadmin or user.
  • C or systems programming experience.
  • Interesting novel perspectives. Can you expand our horizons?

APPLICATION DEADLINE:
Deadline to apply is December 1, 2020.

HOW TO APPLY:
Apply via the instructions on this page. You’ll need to submit the following materials:

  • Current resume
  • Unofficial transcript, including GPA
  • Cover letter describing:
    • Your professional interests, experience, and goals
    • Why you are interested in the Supercomputer Institute
    • How you meet the minimum and desired skills above
    • What you hope to contribute to our team environment

ABOUT LOS ALAMOS:
Los Alamos is a small town in the mountains of northern New Mexico, located an elevation of 7,500 feet.

The town has an active intern community with various events such as free concerts. Outdoor activities are abundant, including hiking, camping, mountain biking, and rock climbing. Summers tend to be warm, and either dry or with afternoon monsoonal thunderstorms.