Optimizing Data Systems for Modern Storage and Memory Technology

Abstract

Data-intensive applications stress the memory hierarchy with unnecessary data movement and the need to integrate new storage technologies. My research addresses these challenges through two main approaches: unlocking the potential of modern storage devices via faithful modeling and minimizing data movement through hardware specialization.

Solid-state drives (SSDs), now dominant in secondary storage, exhibit read/write asymmetry and access concurrency. Most storage-intensive applications overlook these characteristics, leading to suboptimal performance. I propose a new storage modeling approach capturing these properties. Using this model, I develop (i) an asymmetry & concurrency-aware DBMS bufferpool management (that uses the device's write concurrency to amortize the asymmetric write cost), (ii) a concurrency-aware graph manager (that uses the device's read concurrency), and (iii) a reinforcement learning based data placement policy for tiered storage architecture. This paves the way for SSD-aware designs, allowing more systems and components to benefit from this approach.

Moving up the memory hierarchy, data movement is a key bottleneck exacerbated by static layout decisions. To address this, we leverage hardware specialization by developing a custom FPGA-based hardware through software/hardware co-design. Our proposed hardware performs fast on-the-fly data transformation closer to data based on the query access pattern to minimize cache pollution.

In this talk, I will briefly present my research that contributes to (i) the development of data systems components that are tailored for modern SSDs and (ii) building hardware/software co-design approaches that make near-data processing more efficient and scalable.

Biography

Tarikul Islam Papon, a final-year PhD candidate in the Computer Science Department at Boston University (BU), is advised by Manos Athanassoulis. He also served as a graduate-level course instructor at BU. His research focuses on hardware-aware data management challenges, stemming from the evolution of storage and memory devices. During his PhD, he interned at Microsoft Research and Intel Labs. Before joining BU, Papon served as a Lecturer for four years at the CSE Department at Bangladesh University of Engineering and Technology (BUET). He obtained his master's and bachelor's from the same department working on various machine learning and embedded system techniques.