Nomination Deadline:1 May 2020
Next nominations window: March 1 to May 1, 2020
The award committee is selected by the two societies and includes past winners as well as leaders in the field. The Fellowship includes a $5000 honorarium, recognition on the ACM, IEEE CS, and ACM SIGHPC websites, and travel expenses to attend SC. The recipients will be honored at the SC Conference Awards Ceremony
- overall potential for research excellence
- degree to which technical interests align with those of the HPC community
- demonstration of current and planned future use of HPC resources
- evidence of a plan of study to enhance HPC-related skills
- evidence of academic progress to-date, including presentations and publications
- recommendation by faculty advisor
- Name, address, phone number, and email address of nominator (in this case, the candidate is self-nominating).
- Name and contact info for endorser (must be the candidate’s PhD advisor). After the nomination has been submitted, the student will receive an email confirming its receipt. That email will include an encrypted URL which must be forwarded to the advisor. The advisor will use the URL to submit a confidential letter of endorsement (not to exceed 1500 words). Note that it is the candidate’s responsibility to ensure that the advisor (a) receives the endorsement instructions, and (b) submits the endorsement before the deadline.
- Suggested citation if the nomination is selected. This should be a concise statement (maximum of 25 words) describing your research. Note that the final wording for award announcements will be at the discretion of the Award Committee.
- Nomination (PDF not exceeding 5 pages in length, following typical technical paper page standards: 11pt font, single spaced text, fitting within 7.5” x 10” text area). Note that the research interests should be explained in terms understandable to a non-specialist. Only nominations meeting all requirements, including length limitations, will be considered.
- Educational Information (use a table listing each item in a separate row)
- name of educational institution
- name of department
- name of department chair
- enrollment basis (either Full Time or Other; explain if Other)
- year and term PhD program was entered
- most recent GPA
- expected graduation date
- Additional Candidate Information
- o primary telephone
- o alternate telephone
- Statement of Research (2 pp max)
- description of candidate’s research and its importance
- progress to date
- how candidate has used HPC in the past
- plans for the remaining year(s) of graduate study
- Publications, Reports, and Major Presentations
- bibliographic-style listing, including names of all authors in the order they appeared on the title page/slide
- system and environment where performance was measured (1 p max)
ACM/IEEE CS George Michael Memorial HPC Fellowship Committee
- Jack Dongarra, University of Tennessee, (Chair) – CS rep
- Bruce Jacob, University of Maryland – CS Rep
- Susan Rodger, Duke University – CS rep
- Ewa Deelman, USC Information Sciences Institute- CS Rep
- Yves Robert, Institut Universitaire de France – ACM rep
- Tamara Kolda, Sandia Labs – ACM rep
- Ignacio Laguna, Lawrence Livermore National Laboratory (LLNL) – ACM rep
- Karen Karavanic, Portland State University, ACM rep
For his work on high performance algorithms for applications in relativity, geosciences and computational fluid dynamics (CFD).
For her work developing a novel dynamic rerouting algorithm on fat-tree interconnects. The Fellowships are jointly presented by ACM and the IEEE Computer Society.
For her research on fluid dynamics of turbidity currents targeting advancing a 3D-fluid-solver for sedimentation focusing on viscoplastic flow behavior and its methods.
For his research on portable optimizations of complex molecular dynamics codes, utilizing abstraction layers and code generation to obtain high-performance, scalable implementations.
For his work on efficient and parallel large-scale sparse tensor factorization for machine learning applications.
For his work on designing accurate, fast, and scalable machine learning algorithms on distributed systems.
Extreme-Scale Implicit Solver for Nonlinear, Multiscale, and Heterogeneous Stokes Flow in the Earth’s Mantle.
Scalable, Many-core Particle-in-cell Algorithms to Simulate Next Generation Particle Accelerators and Corresponding Large-scale Data Analytics.
His project is entitled "Accelerating Large-Scale Distributed Graph Computations"
His project is entitled "Scalable Algorithms for Evaluating Volume Potentials"
Her project is entitled "Scalable Load Balancing and Adaptive Run Time Techniques"
His project is entitled "Petascale High Order Earthquake Simulations"