Position: PhD Candidate
Current Institution: Harvard University
Abstract: NVMExplorer: A Framework for Cross-Stack Comparisons of Embedded Non-Volatile Memories
Repeated off-chip memory access to DRAM drives up operating power for data-intensive applications and SRAM technology scaling and leakage power limits the efficiency of embedded memories. Future on-chip storage will need higher density and energy efficiency and the actively expanding field of emerging embeddable non-volatile memory (eNVM) technologies is providing many potential candidates to satisfy this need. Each technology specification presents distinct trade-offs in terms of density read write and reliability characteristics and this poster will present a comprehensive framework for navigating and quantifying these design trade-offs alongside realistic system constraints and application-level impacts. To demonstrate the capabilities of this framework I’ll present evaluations of eNVM-based storage for a range of application and system contexts including machine learning on the edge graph analytics and general purpose cache hierarchy in addition to describing the freely available (http://nvmexplorer.seas.harvard.edu/) set of tools for application experts system designers and device experts to better understand compare and quantify the next generation of embedded memory solutions.
Lillian Pentecost is a PhD Candidate in Computer Science at Harvard University advised by Professors David Brooks and Gu-Yeon Wei. Her research enables denser and more efficient future memory systems by exposing and combining design choices in emerging memory devices with architectural support and the demands of critical data-intensive applications like machine learning. Her work includes both specific proposals for integrating and evaluating emerging embedded non-volatile memories and broader methodologies and open-source tools to empower future research. Lillian holds a B.A. in Physics and Computer Science from Colgate University and a S.M. in Computer Science from Harvard University and she has completed research internships at IBM Microsoft and NVIDIA. Additionally Lillian works to integrate the social history and inequities of computing in CS curricula in an effort to increase the emphasis on societal impacts and historical context of technology in computer science education.