Co-Mentors: Volodymyr Kindratenko (Electrical and Computer Engineering) and William Gropp (Computer Science)
Social Impact: Solving larger Big Data problems more quickly, through a new computing platform.
Project description: In this project, students will gain first-hand experience with a cutting-edge computer architecture, Migratory Near Memory Processing Architecture, currently being developed by Emu Technology. This is new technology that could revolutionize several application areas involving big data analytics, many of which have potential social benefits to broad communities. Conventional HPC-scale distributed memory computers are designed with the assumption that the large majority of memory access operations will be to local memory. However, for truly large datasets with complex data access patterns, this is not the case and accessing data across many memory systems becomes necessary to carry out the required computations. Emu’s solution to this problem, referred to as Migratory Memory-Side Processing, is to move the execution context to the data rather than moving large amounts of data to the computational thread. This approach is promising for a number of applications, including both numerical and data-intensive codes.
Emu Technology will provide remote access to a prototype system programmable in Cilk, a parallel language based on C. Students will receive appropriate training in both Cilk programming language and the software development tools and methodologies for Emu’s system. Working with mentors, they will identify 2 to 4 kernels with distinctly different computational workloads and data access patterns and will re-implement them in Cilk for execution on both traditional shared memory systems and on Emu’s novel architecture. Students will carry out the code implementation, performance measurements, and analysis of the results, culminating in a white paper that will compare and contrast applications running on the traditional shared memory architecture and the Migratory Near Memory Processing architecture. The students will work closely with other students at the Innovative Systems Lab (ISL) at NCSA where they will be exposed to other research projects involving novel computer architectures. They will meet with both PIs on a weekly basis to review the results and receive feedback for their work.