I am an Associate Professor of Computer Science at Stony Brook University. I direct the Computer Architecture Stony Brook (COMPAS) Lab. Prior to joining Stony Brook, I completed my Ph.D. at Carnegie Mellon University (CMU) under the supervision of Babak Falsafi. While completing my dissertation, I spent several years working remotely from Ecole Polytechnique Fédérale de Lausanne (EPFL).
My research interests are in the area of computer architecture, with emphasis on the design of server systems. I work on the entire computing stack, from server software and operating systems, to networks and processor microarchitecture. My current research projects include FPGA accelerator integration into server environments (e.g., Intel HARP, Microsoft Catapult, and Amazon F1), FPGA programmability (e.g., virtual memory and high-level synthesis), accelerators for machine learning (e.g., transformers and convolutional neural networks), efficient network processing and software-defined networking, speculative performance and energy-enhancing techniques for high-performance processors, and programming models and mechanisms for emerging memory technologies (e.g., HBM and 3D XPoint).
If you are a PhD student at Stony Brook and want to work with me, please send me email to arrange an appointment.
|||A Case for Specialized Processors for Scale-Out Workloads |
, In IEEE Micro's Top Picks, 2014. (original at ASPLOS'12) [bib] [pdf]
|||Quantifying the Mismatch between Emerging Scale-Out Applications and Modern Processors |
, In ACM Trans. Comput. Syst., ACM, volume 30, 2012. [bib] [pdf]
|||Scale-Out Processors |
, In 39th International Symposium on Computer Architecture (ISCA), 2012. [bib] [pdf]
|||Clearing the Clouds: A Study of Emerging Scale-out Workloads on Modern Hardware |
, In 17th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2012. (recognized as Best Paper by the program committee, recognized as Top Pick of 2013 by IEEE Micro, and received the ACM SIGARCH/SIGPLAN/SIGOPS ASPLOS 2023 Influential Paper Award (test-of-time)) [bib] [pdf]
Computer architecture, with particular emphasis on the design of efficient server systems. Most recently, my main focus has been on Machine Learning Accelerators, developing hardware techniques to enable fast and efficient implementations of deep learning, and making FPGA-based accelerators more practical and easier to program. More broadly, my work seeks to understand the fundamental properties and interactions of application software, operating systems, networks, processor microarchitecture, and datacenter dynamics, to enable software and hardware co-design of high-performance, power-efficient, and compact servers.
These days, it seems like everyone's favorite hobby is to travel. Below is a map that shows the countries I visited.
If you need to speak with me, please feel free to drop by my office at any time. However, to ensure that I will be there and not busy, it's always best to send an email ahead of your visit.
If you prefer to explicitly schedule an appointment, please send me email. You can check my general availability by consulting my calendar.
March 28, 2023: Clearing the Clouds receives the ACM SIGARCH / SIGPLAN / SIGOPS ASPLOS 2023 Influential Paper (test-of-time) Award!
March 23, 2023: Our paper TailCheck: A Lightweight Heap Overflow Detection Mechanism with Page Protection and Tagged Pointers will appear at OSDI'23.
January 25, 2023: Our large-scale study on the feasibility of using Sub-Resource Integrity on the modern web will appear at WWW'23.
June 9, 2022: We received a seed grant to work with BNL on FPGAs for Real-Time ML-Based Data Compression in sPHENIX.
June 8, 2022: The NSF funds our work on Massively Parallel Server Processors.
March 25, 2022: Our work on Dynamic Mantis was published in Bioinformatics.