Alex BreslowComputer Science PhD Student
Advisor: Dean Tullsen
University of California, San Diego
La Jolla, CA
My paper on memory bandwidth conserving, high-performance hash tables has been accepted at USENIX ATC'16.
I am working on a DOE FF2 project at AMD Research. We are exploring architectural and software tradeoffs for a future processor in memory architecture.
For my citation counts, metrics and those of my co-authors, check out my Google Scholar profile.
Alex D. Breslow, Dong Ping Zhang, Joseph L. Greathouse, Nuwan Jayasena, and Dean M. Tullsen. Horton Tables: Fast Hash Tables for In-Memory Data-Intensive Computing. In the Proceedings of USENIX ATC'16. [pdf | slides | bib | ATC'16 talk audio]
Alex D. Breslow, Ananta Tiwari, Martin Schulz, Laura Carrington, Lingjia Tang, and Jason Mars. Enabling Fair Pricing on HPC Systems with Node Sharing. In the Proceedings of SC'13. Best Paper Finalist and Best Student Paper Finalist[pdf | bib]
Alex D. Breslow, Leo Porter, Ananta Tiwari, Michael A. Laurenzano, Laura Carrington, Dean M. Tullsen, and Allan E. Snavely. The Case for Colocation of HPC Workloads. Concurrency and Computation: Practice and Experience; Special issue on the Analysis of Performance and Power for Highly Parallel Systems (CCPE 2013). [pdf | bib]
Andrew Danner, Jake Baskin, Alexander Breslow, and David Wilikofsky. Hybrid MPI/GPU Interpolation for Grid DEM Construction. In Proc. ACM Symposium on Advances in Geographic Information Systems, pages 299-308, 2012. [pdf | bib]
I primarily work in the areas of parallel and distributed computing, computer architecture, and computer systems. Most of my work has focused on improving the performance, energy efficiency, and utilization of data centers and supercomputers. Recently, I have been doing work on bottleneck analysis of core primitives from columnar in-memory databases on GPUs as well as optimizing hash tables for bandwidth-constrained systems. This more recent work has been conducted at AMD Research as part of a U.S. Department of Energy Fast Forward2 project on near-data computing.My advisor is Dean Tullsen.