Martin Maas

Research Scientist, Google Brain

1600 Amphitheatre Pkwy, Mountain View, CA

E-Mail: <firstname>

I am a Research Scientist in the Google Brain team. Before joining Google, I completed my PhD in the Electrical Engineering and Computer Sciences department at UC Berkeley, working with Krste Asanović and John Kubiatowicz. My primary research interests are in managed language runtime systems, operating systems and computer architecture. I am interested in the entire stack from the hardware to the programming systems layer. At Google Brain, I am working on topics related to machine learning.

My PhD research focused on warehouse-scale computers. I worked and collaborated across areas and built real systems that involve large system-level codebases as well as hardware-level RTL. I have applied this approach to domains ranging from security to managed languages. During my PhD, I built a secure processor that provides memory-trace obliviousness (a new security property) and can be targeted by a custom compiler, a distributed language runtime system that coordinates JVMs on different nodes in a cluster, and worked on hardware support for garbage collection. I have also built research infrastructure, including FPGA implementations of hardware based on the RISC-V ISA.

Before coming to UC Berkeley, I completed my undergraduate degree at the University of Cambridge. In my undergraduate research, I investigated the challenges and bottlenecks of implementing a Java Virtual Machine for the Barrelfish Operating System. I was supervised by Ross McIlroy and Tim Harris from Microsoft Research, Cambridge.

During my time in high-school, I was an active participant in science and programming competitions. I was on the German team for the International Olympiad of Informatics (IOI) and represented Germany at the International Science and Engineering Fair (ISEF).

  • Learning-based Memory Allocation for C++ Server Workloads, Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel, International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '20), Lausanne, Switzerland, March 2020 (to appear)
  • Multi-Task Learning for Storage Systems, Giulio Zhou, Martin Maas, Workshop on ML for Systems at NeurIPS 2019, Vancouver, Canada, December 2019 Paper
  • A Hardware Accelerator for Tracing Garbage Collection, Martin Maas, Krste Asanović, John Kubiatowicz, 45th International Symposium on Computer Architecture (ISCA'18), Los Angeles, California, June 2018 Paper (Selected as one of IEEE Micro's Top Picks from the 2018 Computer Architecture Conferences)
  • Taurus: A Holistic Language Runtime System for Coordinating Distributed Managed-Language Applications, Martin Maas, Krste Asanović, Tim Harris, John Kubiatowicz, International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '16), Atlanta, Georgia, April 2016 Paper
  • Trash Day: Coordinating Garbage Collection in Distributed Systems, Martin Maas, Tim Harris, Krste Asanović, John Kubiatowicz, 15th Workshop on Hot Topics in Operating Systems (HotOS '15), Kartause Ittingen, Switzerland, May 2015 Paper
  • GhostRider: A Hardware-Software System for Memory Trace Oblivious Computation, Chang Liu, Austin Harris, Martin Maas, Michael Hicks, Mohit Tiwari, Elaine Shi, International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '15), Istanbul, Turkey, March 2015 Paper (Winner of the Best Paper Award)
  • Callisto: Co-Scheduling Parallel Runtime Systems, Tim Harris, Martin Maas, Virendra Marathe, ACM European Conference on Computer Systems (EuroSys '14), Amsterdam, Netherlands, April 2014 Paper
  • PHANTOM: Practical Oblivious Computation in a Secure Processor, Martin Maas, Eric Love, Emil Stefanov, Mohit Tiwari, Elaine Shi, Krste Asanović, John Kubiatowicz, Dawn Song, ACM Conference on Computer and Communications Security (CCS '13), Berlin, Germany, November 2013 Paper (Finalist for NYU-Poly (formerly AT&T) Best Applied Security Paper Award 2013)
  • GPUs as an Opportunity for Offloading Garbage Collection, Martin Maas, Philip Reames, Jeffrey Morlan, Krste Asanović, Anthony D. Joseph, John Kubiatowicz, International Symposium on Memory Management (ISMM '12), Beijing, China, June 2012 Paper

Last updated: January 2020