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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Carnegie-Mellon University |
| Country | United States |
| Start Date | Jun 01, 2021 |
| End Date | May 31, 2025 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2107307 |
Lightweight virtualization technologies such as containers have enabled emerging computing paradigms of microservices and serverless computing with thousands of concurrent users sharing each server. Unfortunately, current compiler, hardware, and operating systems were optimized for the steady state of long running applications instead of the very short-lived execution of functions.
Especially in the current era of multi-core processors, existing context management mechanisms impose significant performance overheads. Furthermore, serverless environments are dominated by ephemeral state (e.g., intermediate computations) and containers that are discarded after function invocation is complete. Nevertheless, existing system stacks do not take into account the ephemeral nature of serverless computing.
The goal of this project is to design new hardware and operating system execution contexts in synergy with compiler optimizations to match the needs of function computation. This work will build new compiler techniques for function analysis to identify the data needs of ephemeral execution. In addition, this project will explore a new cross-stack interface that allows the communication and ephemeral state tracking at the operating system and hardware layers.
Finally, this work will explore the design of hardware support for managing compiler-identified ephemeral data through novel hardware contexts purposefully built for function execution that will aim to minimize data movement and energy consumption.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Carnegie-Mellon University
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