EE260: Trends in Computer System Design


Hung-Wei Tseng
email: htseng @
Office Hours: WTh 1p-2p @ WCH 406

Course Overview

As Dennard Scaling restricts the performance gain from microprocessors generation-by-generation, the system design needs to exploit new programming and execution models to fulfill the rapid growth in the demand of computation and data storage. Recent developments of computer systems show a few trends that are quite different from the conventional approach. These trends are:

This course will study the opportunities and challenges created by these trends. We will study several real system implementations based on these trends and discuss the problem they solved as well as new issues they created. Since this course relies on recent research papers to provide the materials for case studies, this class will additionally provide the following learning agendas for students:


This class will require the students to read/discuss two research papers from recent top-tier computer architecture, computer systems, embedded systems, programming language/compiler conferences.


Schedule and Slides

ReadingSlides (Release)Note
1/14/2020RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics
Jacob Sacks, Divya Mahajan, Richard C. Lawson and Hadi Esmaeilzadeh. ISCA 2018
1/21/2020In-Memory Data Parallel Processor
Daichi Fujiki , Scott Mahlke and Reetuparna Das. ASPLOS 2018

Extension Framework for File Systems in User space
Ashish Bijlani and Umakishore Ramachandran. USENIX ATC 2019

1/28/2020TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory
Mingyu Gao, Jing Pu, Xuan Yang Mark, Horowitz and Christos Kozyrakis

Tigris: Architecture and Algorithms for 3D Perception in Point Clouds.
Tiancheng Xu, Boyuan Tian, Yuhao Zhu (University of Rochester).
MICRO 2019
2/4/2020Shape-Programmable Soft Capsule Robots for Semi-Implantable Drug Delivery
Sehyuk Yim and Metin Sitti (CMU)
IEEE Transaction in Robotics, 2012

LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation.
Yizhou Shan, Yutong Huang, Yilun Chen, and Yiying Zhang (Purdue University).
USENIX OSDI 2018 (Best Paper)
2/11/2020Cognitive SSD: A Deep Learning Engine for In-Storage Data Retrieval
Shengwen Liang and Ying Wang, State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing; University of Chinese Academy of Sciences; Youyou Lu and Zhe Yang, Tsinghua University; Huawei Li and Xiaowei Li, State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing; University of Chinese Academy of Sciences

GraFBoost: Using accelerated flash storage for external graph analytics
Sang-Woo Jun, Andy Wright, Sizhuo Zhang, Shuotao Xu, Arvind. ISCA 2018
2/18/2020SMASH: Co-designing Software Compression and Hardware-Accelerated Indexing for Efficient Sparse Matrix Operations.
Konstantinos Kanellopoulos, Nandita Vijaykumar, Christina Giannoula, Roknoddin Azizi, Skanda Koppula, Nika Mansouri Ghiasi, Taha Shahroodi, Juan Gomez Luna, and Onur Mutlu. MICRO 2019
An Experimental Microarchitecture for a Superconducting Quantum Processor
X. Fu, M. A. Rol, C. C. Bultink, J. van Someren, N. Khammassi, I. Ashraf, R. F. L. Vermeulen, J. C. de Sterke, W. J. Vlothuizen, R. N. Schouten, C. G. Almudever, L. DiCarlo, and K. Bertels. MICRO 2017
2/27/2020Statistical assertions for validating patterns and finding bugs in quantum programs.
Yipeng Huang and Margaret Martonosi. ISCA 2019
G-TSC: Timestamp Based Coherence for GPUs
Abdulaziz Tabbakh, Xuehai Qian, Murali Annavaram. HPCA 2018
3/3/2020Edge Assisted Real-time Object Detection for Mobile Augmented Reality
Luyang Liu, Hongyu Li and Marco Gruteser. MobiCOM 2019

A DNA-Based Archival Storage System.
James Bornholt, Randolph Lopez, Douglas M. Carmean, Luis Ceze, Georg Seelig, and Karin Strauss. ASPLOS 2016
3/10/2020Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks. M. Rhu, M. O’Connor, N. Chatterjee, J. Pool, Y. Kwon and S. W. Keckler. HPCA 2018
On-Line Event-Driven Scheduling for Electric Vehicle Charging via Park-and-Charge. F. Kong, Q. Xiang, L. Kong and X. Liu. RTSS 2016
RT-IFTTT: Real-Time IoT Framework with Trigger Condition-Aware Flexible Polling Intervals. S. Heo, S. Song, J. Kim and H. Kim. RTSS 2017