Martin Maas

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 18

Top Topics

Resource Management

Trained Neural Networks

Storage Systems

Garbage Collection

Top Venues

Publications

Phitchaya Mangpo Phothilimthana, Saurabh Kadekodi, Soroush Ghodrati, Selene Moon, Martin Maas
Thesios: Synthesizing Accurate Counterfactual I/O Traces from I/O Samples. ASPLOS (3) (2024)
Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel
Combining Machine Learning and Lifetime-Based Resource Management for Memory Allocation and Beyond. Commun. ACM 67 (4) (2024)
Christian Navasca, Martin Maas, Petros Maniatis, Hyeontaek Lim, Guoqing Harry Xu
Predicting Dynamic Properties of Heap Allocations using Neural Networks Trained on Static Code: An Intellectual Abstract. ISMM (2023)
Martin Maas, Ulysse Beaugnon, Arun Chauhan, Berkin Ilbeyi
TelaMalloc: Efficient On-Chip Memory Allocation for Production Machine Learning Accelerators. ASPLOS (1) (2023)
Zixian Cai, Stephen M. Blackburn, Michael D. Bond, Martin Maas
Distilling the Real Cost of Production Garbage Collectors. ISPASS (2022)
Paras Jain, Safeen Huda, Martin Maas, Joseph E. Gonzalez, Ion Stoica, Azalia Mirhoseini
Learning to Design Accurate Deep Learning Accelerators with Inaccurate Multipliers. DATE (2022)
Binghong Chen, Daniel Tarlow, Kevin Swersky, Martin Maas, Pablo Heiber, Ashish Naik, Milad Hashemi, Parthasarathy Ranganathan
Learning to Improve Code Efficiency. CoRR (2022)
Martin Maas, Chris Kennelly, Khanh Nguyen, Darryl Gove, Kathryn S. McKinley, Paul Turner
Adaptive huge-page subrelease for non-moving memory allocators in warehouse-scale computers. ISMM (2021)
Zixian Cai, Stephen M. Blackburn, Michael D. Bond, Martin Maas
An Empirical Lower Bound on the Overheads of Production Garbage Collectors. CoRR (2021)
Leon Sixt, Evan Zheran Liu, Marie Pellat, James Wexler, Milad Hashemi, Been Kim, Martin Maas
Analyzing a Caching Model. CoRR (2021)
Giulio Zhou, Martin Maas
Learning on Distributed Traces for Data Center Storage Systems. MLSys (2021)
Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel
Learning-based Memory Allocation for C++ Server Workloads. ASPLOS (2020)
Martin Maas
Hardware support for managed languages: an old idea whose time has finally come? (keynote). MPLR (2020)
Martin Maas
A Taxonomy of ML for Systems Problems. IEEE Micro 40 (5) (2020)
Martin Maas, Krste Asanovic, John Kubiatowicz
A Hardware Accelerator for Tracing Garbage Collection. IEEE Micro 39 (3) (2019)
Martin Maas, Krste Asanovic, John Kubiatowicz
A Hardware Accelerator for Tracing Garbage Collection. ISCA (2018)
Martin Maas, Krste Asanovic, John Kubiatowicz
Return of the Runtimes: Rethinking the Language Runtime System for the Cloud 3.0 Era. HotOS (2017)
Martin Maas, Krste Asanovic, Tim Harris, John Kubiatowicz
Taurus: A Holistic Language Runtime System for Coordinating Distributed Managed-Language Applications. ASPLOS (2016)
Chang Liu, Austin Harris, Martin Maas, Michael W. Hicks, Mohit Tiwari, Elaine Shi
GhostRider: A Hardware-Software System for Memory Trace Oblivious Computation. ASPLOS (2015)
Martin Maas, Tim Harris, Krste Asanovic, John Kubiatowicz
Trash Day: Coordinating Garbage Collection in Distributed Systems. HotOS (2015)
Tim Harris, Martin Maas, Virendra J. Marathe
Callisto: co-scheduling parallel runtime systems. EuroSys (2014)
Martin Maas, Eric Love, Emil Stefanov, Mohit Tiwari, Elaine Shi, Krste Asanovic, John Kubiatowicz, Dawn Song
PHANTOM: practical oblivious computation in a secure processor. CCS (2013)
Martin Maas, Philip Reames, Jeffrey Morlan, Krste Asanovic, Anthony D. Joseph, John Kubiatowicz
GPUs as an opportunity for offloading garbage collection. ISMM (2012)