Theme 2: Distributed Evolvable Memory and Storage
The computing infrastructure will include highly-heterogeneous distributed memory and storage resources. As workloads relentlessly increase their data needs, the memory reachable by processors as local memory will expand across an entire rack–creating a formidable memory wall that we will meet with novel processor structures and gracefully-degrading coherence mechanisms. To utilize heterogeneous memory and storage assets efficiently, we will develop new abstractions that allow applications to select the type of asset needed. Moreover, we will develop theory-grounded scalable algorithms to apportion these assets efficiently among thousands of competing applications in the datacenter and billions of allocation requests. Ubiquitous intelligent memory and storage blocks distributed across the memory hierarchy will be harnessed to operate in a coordinated manner.
Papers and Presentations:
Snapshot: Fast, Userspace Crash Consistency for CXL and PM Using msync
Suyash Mahar, Mingyao Shen, Terence Kelly, Steven Swanson
2023 IEEE 41st International Conference on Computer Design (ICCD)
10.1198/ICCD58817.2023.00082
Profiling gem5 Simulator
Johnson Umeike, Neel Patel, Alex Manley, Amin Mamandipor, Heechul Yun, Mhommad Alian
IPASS 2023
10.1109/ISPASS57527.2023.00019
2024
EdgeScaler:Smart (Auto-)Scaling for the 5G Edge
Lauren Trinks, Bilal Saleem, Muhammad Shahbaz
APSys 2024
Per-Bank Bandwidth Regulation of Shared Last-Level Cache for Real-Time Systems
C. Sullivan, A. Manley, M. Alian and H. Yun
2024 IEEE Real-Time Systems Symposium (RTSS)
10.1109/RTSS62706.2024.00036
FloatAP: Supporting High-Performance Floating-Point Arithmetic in Associate Processors
Kailin Yang, Jose Martinez
2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO)
10.1109/MICRO61859.2024.00055
Telepathic Datacenters: Fast RPCs using Shared CSL Memory
Suyash Mahar, Ehsan Hajyjasini, Seungjin Lee, Zifeng Zhang, Mingyao Shen, Steven Swanson
arXiv:2408.11325
Userspace Networking in gem5
J. Umeike, S. Agarwal, N. Lazarev and M. Alian
2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
10.1109/ISPASS61541.2024.00026
Caravan: Practical Online Learning of In-Network ML Models with Labeling Agents
izheng Zhang, Ali Imran, Enkeleda Bardhi, Tushar Swamy, Nathan Zhang, Muhammad Shahbaz, Kunle Olukotun
PACMI '24: Proceedings of the 3rd Workshop on Practical Adoption Challenges of ML for Systems
10.1145/3704742.3704964