Hao Zhuang - Computer Science and Engineering, University of California, San Diego

Computer Science & Engineering Department, University of California, San Diego, CA, USA Mailing: 9500 Gilman Dr., EBU3, CSE Dept., La Jolla, CA, 92093-0404 E-mail: hao.zhuang [at] cs.ucsd.edu External Acadmeic Profiles: Google Scholar, DBLP, Code hub (there are hidden projects): me@github, me@bitbucket; Misc: me@wordpress topcoder codeforces

We have been building numerical solvers for large-scale optimization and simulation software to help very large-scale integration designs. Many ideas are borrowed from the areas of matrix computation, optimization and machine learning. Interestingly, we still frequently use at least 4 out of the top 10 algorithm in 20th century.

Current Research Interests:

numerical algorithms, numerical optimizations, nonlinear optimization, nonlinear simulation, circuit simulation, learning, and large-scale computing system for design automation algorithm and applications to computer hardware, also known as another kind of solving large-scale problem (think about the number of transistors in a chip as the problem size). I am also opened to the challenges from distributed computing systems and large-scale numerical algorithms, as well as high performance programming language and compiler (early stage). I enjoy research on differential equations and optimization problems in applied mathematics.

Updates

• Feb. 2015: One paper got accepted by the top-tier EDA conference ACM/IEEE Design Automation Conference (DAC) 2015, San Francisco, CA.

• Nov. 2014: (1) Our journal paper about VLSI physical design placement (ePlace) using one of accelerated gradient methods – Nesterov's optimization algorithm and FFT solver got accepted by the top-tier EDA journal IEEE Trans. CAD (TCAD); (2) Served as the computer system administrator at the VLSI design lab. I am currently the system programmer of the internal system - feynman dot ucsd dot edu.

• Sep. 2014: Became 3rd year PhD student at CSE Dept., UCSD.

• June 2014: (1) Attended ACM/IEEE DAC 2014, and presented the work [pdf] [slides] to simulate power grid network using matrix exponential integrators, Krylov subspace algorithms, and its distributed computation framework. (2) Passed UCSD CSE Ph.D's research exam (Committee members: Prof. Steven Swanson (chair), Prof. Sanjoy Dasgupta, and Prof. Lawrence Saul). (3) Started R&D software engineering intern at Synopsys, Inc., and to live at the campus of Stanford University at the end of month. (4) Gave a research talk at Synopsys, Inc.

• Apr. 2014: Attended UC San Diego Jacob School of Engineering's Research Expo

• Feb. 2014: One paper got accepted by the top-tier ACM/IEEE Design Automation Conference (DAC) 2014, San Francisco, CA, thanks my co-authors, Dr. S.-H. Weng (now a research scientist with Facebook, Inc.) and J.-H. Lin, and Prof. C. K. Cheng.

• Dec. 2013: Gave a talk on matrix exponential based circuit simulation in EDA Lab, Tsinghua University, hosted by Prof Wenjian Yu.

• May 2013: Our lab was awarded with Qualcomm FMA Fellowship.

• Sep. 2012: Joined Computer Science & Engineering Department, University of California, San Diego, CA.

• Jul. 2012: Graduated from Peking University, Beijing, China, and finished the joint research work with Tsinghua University.

• Feb. 2012: Awarded with Charles Lee Powell Fellowship.

Publications/Reports

Please note that papers linked here represent author preprints or updated drafts. The official, published version must be obtained from the publisher's website or the published print copy. This material is presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each document's copyright terms. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Permission is given to make digital or hard copies of all or part of this material without fee for personal or classroom use, provided that the copies are not made or distributed for profit or commercial advantage, and that copies bear the appropriate copyright notice and the full bibliographic citation on the first page. Copyrights for components of this work owned by others must also be honored. To copy otherwise, to republish, to post on servers, to redistribute to lists, etc. requires specific permission and/or a fee. In particular, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the copyright owner. Please note further that any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsoring agencies, employers, or publishers.

Conferences:

(Top-tier and good conferences: DAC, ICCAD and DATE, ASP-DAC)

Journals:

(Top-tier journals: TCAD)

Other Technical Notes

Research Projects

• Circuit Simulation Algorithms and its Parallel/Distributed Processing, Applications of Power Network Analysis (Mar. 2013 - present)
  Description: “To analyze and verify VLSI systems via full circuit simulation and to demonstrate vastly improved scalability in order to raise the quality and scope of predictive circuit modeling. VLSI circuit simulation has become critical due to interconnect dominance of advanced fabrication technologies. Functional modules are integrated through substrates and connected by wires with parasitics. A simulation of the whole system will empower designers with a full grasp of the transient behavior of the circuits.” Keywords: Matrix Exponential, Krylov Subspace, Distributed Computing, Parallel Computing, VLSI Design and Analysis, Numerical Algorithms, Differential Equations, Compact Modeling, GPU, Power Distribution Networks, Power Delievery Networks, ASIC design.
  Papers: [DAC15] [DAC14] [EMC15] [ASICON13]
  Stay tuned
  

• Design and Design Automations in Placement, Synthesis of 2D/3D-ICs (Jun. 2013 - present) [ePlace project website]
  Description: Design automation algorithms to investigate the floorplanning and synthesis for 2D/3D integrated circuits. The goal is to extract and manipulate the topology of 2D/3D geometry for physical layout. We mimic the electrostatics for placement problem, and use optimization algorithms to reduce the compoiste objective functions. The placement solver also smartly adopts fast Fourier transformation (FFT) to accelerate its optimization process (The 2D placement algorithm research is supported by Cadence System Design). The design automation research for future computer architecture using 3D-ICs is also supported by Qualcomm FMA fellowship 2013. Keywords: Physical Design, Placement, ePlace, Nesterov's Method, FFT, Linear and Nonlinear Programming, Combinatorial Optimization, VLSI Design, VLSI Synthesis, Computer Architecture, Interconnect Network.
  Papers: [TCAD15] [ICCCAS13]
  

• Stochastic Algorithms for VLSI chip parasitic extraction field solver (Feb. 2011 - Jul. 2012) [RWCap project website] and [RWCap2 new project webiste]
  Description: To extract capacitance parameters in VLSI design by devising floating random walk algorithms. This method improves scalability and efficiency for large-scale numerical problems. Some pratical software packages have been developed. Keywords: Floating Random Walk Algorithms, Multi-thread Programming, GPU, 3D Space Management, Importance/Stratified Sampling, Monte Carlo Algorithm.
  Papers: [TCAD13] [SMPT13] [DATE13] [ASPDAC12] [ASICON11]
  

Software

Patents

• GPU-based system and method for extracting capacitance parameter of integrated circuit (pending) Jul 10, 2013

• IC design calculation method based on extracting the capacitance parameter random walk Dec 11, 2013

Research and Working Expeirence

Services

Teaching

• Assistant, CSE245: Numerical Algorithms and Circuit Simulation (2015 Winter)

• Teaching Assistant, CSE140: Components and Design Techniques for Digital Systems (2014 Autumn)
  -- Textbook: Digital Design and Computer Architecture (2nd Edition) by David Mooney Harris and Sarah L. Harris

Selected Honors

• Qualcomm FMA Fellowship (2014).

• Charles Lee Powell Fellowship (2013, 2015).

• Peking University Wusi Scholarship (2011).

Selected Courses

Computer Science (CS)

• CSE202: Algorithms and Data Structures (Prof. Russell Impagliazzo)
  -- Project: Cache-Oblivious Algorithm and Data Structures.
  -- [Solution] of final
  

• CSE230: Programming Language (Prof. Ranjit Jhala)
  -- Actually, it is a functional language course, talking about Haskell.
  

• CSE231: Advanced Compilers (Prof. Sorin Lerner)
  -- Final Project: Verilog Generation of Sub-Blocks within UCSD Conservation Cores Architecture (using LLVM, within Prof. Micheal Taylor's group) [slides].
  

• CSE240: Principles in Computer Architecture (Prof. Dean Tullsen)
  -- Project 1: Branch Predictor Design and Simulation.
  -- Project 2: Cache Design and Simulation.
  

• CSE120: Principles of Operating Systems (Prof. Joseph Pasquale)
  -- Have fun with xv6@MIT and qemu by self.
  

• CSE260: Parallel Computation (Prof. Scott Baden)
  -- Final Project: Parallel Matrix Vector Multiplication using MPI [report].
  -- Also learn about GPU, CUDA, OpenMP, pthread, MPI.
  

• CSE223B: Distributed Computing and Systems (Prof. Alex Snoeren)
  --Final Project (the top-ranked project in the class): Trusted Bridge - Online Distributed Synchronized Storage Systems (using C++, node.js, python), we wrote a simple online storage systems, also interacted with Dropbox API, Google Drive API for storage aggregations [report]. Afterwards, thanks to my classmates’ great efforts (excluding me), the prototype now transits to TrustedBridge product.

• CSE250B Machine Learning (Prof. Sanjoy Dasgupta)
  

• CSE105: Automata and Computability Theory (Prof. Hovav Shacham)
  

Mathematics

• MATH270B: Numerical Approximation and Nonlinear Equations (Prof. Michael Holst)
  

• MATH270C: Numerical Oridinary Equations (Prof. Melvin Leok)
  -- Classical algorithms on differential equations.
  

• MATH: Complex Analysis
  

• MATH: Real Analysis
  -- Inspired by the understanding of Lebesbegue integration and statistical notion of integration, and apply importance sampling to RWCap.

Electrical Engineering (EE)

• CSE245: Circuit Simulation (Prof. Chung-Kuan Cheng)
  -- Final Project: Linear Circuit Simulation using Matrix Exponential Method with Rational Krylov Subspaces, which becomes a part of paper accepted by IEEE Intl. Conf. on ASIC 2013.

• CSE291: High Performance Interconnects (Prof. Chung-Kuan Cheng)
  -- Seminar's topics on networks from data center servers wiring to on-chip interconnects.

• EECS: Semiconductor Device Physics and Fabrication Technologies (Prof. Ru Huang and Prof. Xing Zhang)
  -- MOS Device physics and fabrications.

• EECS: Digital Circuits and Systems (Prof. Xiaoyan Liu)
  -- Final Project: Adder Design and Optimization

• EECS: VLSI Design (Prof. “Grandma” Xuewen Gan)

Misc.

My education background dangles in EECS and Applied Math. Thanks to the people around in CS/EE/Math departments and even my roommates, who bring to me the beauty of theoritical parts of kernel solvers, numerical solvers, optimizers, machine learning as well as their applications on computer systems designs, programming.
I am a fan of C/C++, Javascript, Node.js and MATLAB, sometimes use Python, Haskell and play around with LLVM for Compiler and Computer Architecture.

“But it's the human time that in the end matters the most.” by MIT News HPC with ease

Links and Useful Notes (at least to me)

• Advanced Data Structures

• How to Do Research by Prof Yi Ma, UIUC and Microsoft Research Asia

• Matlab Hacks by Dr. Richard Socher @ Stanford

• RPC and NFS by Prof. David Mazieres

• dropbox's project – pyston

• NFS and User-level file systems by Prof. David Mazieres

• Circuit simulation tutorial by Dr. Kundert

• System Programming by Prof. X. Wang

• The book Numerical Algorithms by Justin Solomon

• Stanford EE364B: Convex Optimization II by Prof. S. Boyd

• Codechef, HackerEarth, HackerRank.

• Stanford CS231n: Convolutional Neural Networks for Visual Recognition by Prof. Li Fei-Fei and Andrej Karpathy