EE260: Trends in Computer System Design
email: htseng @ ucr.edu
Office Hours: WTh 1p-2p @ WCH 406
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:
- Holistic/cross-layered system design instead of single-point/local optimizations.
- Distributed computing instead of centralized computing.
- Massive, wimpy processing units instead of single, powerful processing unit.
- Domain-specific design instead of general-purpose architectures.
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:
- How to read a research paper in an objective manner.
- How to articulate your understanding of and insights into a research paper.
- How to synthesize research themes and topics across multiple papers.
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.
- 50% Presentation
This course will require each student to give a 20-minute, conference-style presentation at least once on a research paper within the quarter
- 30% Paper analysis
This course will require each student to review and evaluate the intellectual merits, strength, weakness of a set of self-selected papers that fits both the student’s research topic and the agenda of the class
- 20% Class participation and discussion
This class will require students to attend and discuss the studied research paper every week.
Schedule and Slides
|1/14/2020||RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics|
Jacob Sacks, Divya Mahajan, Richard C. Lawson and Hadi Esmaeilzadeh. ISCA 2018
|1/21/2020||In-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
|1/28/2020||TETRIS: 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).
|2/4/2020||Shape-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)
|2/11/2020||Cognitive 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
|2/18/2020||SMASH: 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
|2/27/2020||Statistical 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
|3/3/2020||Edge 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
|3/10/2020||Compressing 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