NCSA Position Notice -- Graduate Research Assistant

Graduate Research Assistant

Blue Waters Project Office

Overview

This project deals with the static and dynamic optimization of communication schedules. Communication schedules are a set of communication operations and dependencies and define an order of their execution. A set of such operations and dependencies form a global communication graph. The goal of this project is to optimize the communication graph in a given model (e.g., LogGP) and to compare the quality of solutions.

For example, a broadcast communication from node 0 to nodes 1..3 can be expressed as the set {(0,1), (0,2), (0,3), (0,4)} (where a tuple (x,y) represents communication from x to y) or {(0,1}, (1,3), (0,2)} in a tree-like shape. Using a broadcast tree is more efficient in this trivial example. The project aims to develop model-based optimization techniques for the optimization of such communication operation represented in the tuple-form above. The main work is to develop and proof optimality of algorithms working on this tuple-form using well-known communication models such as LogGP.

Reaching optimality is generally very hard. We plan to follow three avenues: (1) analytical algorithms and proofs, (2) well-known optimization methods (linear or integer optimization), and (3) heuristics and learning-based methods. The results should be implemented in an MPI-like library.

For more details and references see the project webpage http://www.unixer.de/research/compi/.

Required Skills

The student working on this project should know what MPI is, be familiar with the C and C++ programming languages and he should be very familiar with linear optimization, (mixed) integer programming and basic network models. The student should understand the papers Alexandrov et al. "LogGP: incorporating long messages into the LogP model—one step closer towards a realistic model for parallel computation" and Bruck et al. "Efficient Algorithms for All-to-All Communications in Multi-Port Message-Passing Systems" well.

This graduate research assistant position is a 50% appointment, starting ASAP and is paid monthly. The salary rate is dependent on graduate status (qual/non-qual) and this position is tuition waiver eligible. Please apply via email to Torsten Hoefler, htor@illinois.edu.

Illinois is an Affirmative Action/Equal Opportunity Employer and welcomes individuals with diverse backgrounds, experiences, and ideas who embrace and value diversity and inclusivity. For further information regarding our application procedures, you may visit www.ncsa.illinois.edu or email Jonathan Howell.