LSSG Openings (updated 9/15/2018)


Postdocs, Graduate Students, and Undergraduate Students
  • Challenges to Scaling Cloud Computing: Gigantic power consumption and Grid transformation to volatile Renewable Generation
    Cloud computing is the fastest growing consumer of electric power in the world! This is a challenge for the continued growth of the Hyperscalers (Google, FB, Microsft, Amazon, Alibaba, Baidu, Apple, etc.). We study opportunities to make distributed systems more flexibly reliable -- allowing them to exploit "Opportunity power" or "Stranded power" produced by power markets, and rising levels of volatile renewable generation. Topics include distributed systems, resource management, new volatile services models, serverless, power markets, power grids.

  • Computing the Representation to optimize Data Movement and Storage
    Its widely recognized that data movement (from memory, from SSD, within a parallel machine, even in the wires across a chip) is the critical cost and performane limiter in computer systems. We are studying architectures that enable efficient rapid transformation of information encodings, to reduce size and computation cost. Initial designs and studies show that benefits of 4x to 1000x can be achieved in specific cases. Critical challenges include how to expose these new ideas to software: (e.g. transformer libraries, or to view C++ arrays as abstract data types with a different concrete type implementation), as well as a variety of functional and implementation architecture issues. The space for this radical changes has just begun to be explored. We are working with several agencies to build large scale prototypes (1000's of nodes) within the next 3-5 years.

  • Data-intensive computing, Scalable In-memory analytics In-situ Data Analytics
    Application of efficient data transformation accelerators to produce breakthrough data analytics performance (10-100x absolute performance and power efficiency). Topics include filtering, RAW processing, efficient ETL, predicate push-down, and query optimization. Current work is in SparkSQL with at-scale experiments on a variety of novel accelerator platforms.
  See our LSSG group homepage  for more background, and if you are interested, email Professor Andrew A. Chien.

The  LSSG is affiliated with the CERES Center and is part of the  Systems Group  in the University of Chicago's Department of Computer Science , and also affiliated with Argonne National Laboratory's  Mathematics and Computer Science Division.