Resume

• 2010

  Chinese

  English

  Ph.D

  Electrical and Computer Engineering

  Student volunteer at SC11

  Reviewer at 29th IEEE International Conference on Computer Design (ICCD 2011)

  The George Washington University

• 2008

  Electrical & Computer Engineering

  Colorado State University

• 1999

  Master of Science

  Computer Science & Information Engineering

  National Chung Cheng University

• 1995

  Bachelor

  Computer Science & Information Engineering

  Tamkang University

• Algorithms

  Linux

  Programming

  LaTeX

  Perl

  Shell Scripting

  Optimization

  Operating Systems

  Machine Learning

  Matlab

  Cloud Computing

  Distributed Systems

  ARM

  Virtualization

  C

  Architectures

  Java

  Embedded Systems

  Assembly

  Python

  IOrchestra: Supporting High-Performance Data-Intensive Applications in the Cloud via Collaborative Virtualization

  Multi-tier data-intensive applications are widely deployed in virtualized data centers for high scalability and reliability. As the response time is vital for user satisfaction

  this requires achieving good performance at each tier of the applications in order to minimize the overall latency. However

  in such virtualized environments

  each tier (e.g.

  application

  database

  web) is likely to be hosted by different virtual machines (VMs) on multiple physical servers

  where a guest VM is unaware of changes outside its domain

  and the hypervisor also does not know the configuration and runtime status of a guest VM. As a result

  isolated virtualization domains lend themselves to performance unpredictability and variance. In this paper

  we propose IOrchestra

  a holistic collaborative virtualization framework

  which bridges the semantic gaps of I/O stacks and system information across multiple VMs

  improves virtual I/O performance through collaboration from guest domains

  and increases resource utilization in data centers. We present several case studies to demonstrate that IOrchestra is able to address numerous drawbacks of the current practice and improve the I/O latency of various distributed cloud applications by up to 31%.

  IOrchestra: Supporting High-Performance Data-Intensive Applications in the Cloud via Collaborative Virtualization

  howie huang

  Scalability challenges of DRAM technology call for advances in emerging memory technologies

  among which Phase Change Memory (PCM) has received considerable attention due to its non-volatility

  storage density and capacity advantages. The drawbacks of PCM include limited write endurance and high power consumption for write operations (upto 10x in comparison to read operations). In this paper

  we investigate new techniques that would perform writes to PCM with energy awareness. Our results show that we can minimize the write energy consumption by up to 8.1x by simply converting PCM native writes to read-before-write

  and upto an additional 22.9% via intelligent out-of-position updates.

  Energy-Aware Writes to Non-Volatile Main Memory

  howie huang

  Scalability challenges of DRAM technology call for advances in emerging memory technologies

  among which Phase Change Memory (PCM) has received considerable attention due to its non-volatility

  storage density and capacity advantages. The drawbacks of PCM include limited write endurance and high power consumption for write operations (upto 10x in comparison to read operations). In this paper

  we investigate new techniques that would perform writes to PCM with energy awareness. Our results show that we can minimize the write energy consumption by up to 8.1x by simply converting PCM native writes to read-before-write

  and upto an additional 22.9% via intelligent out-of-position updates.

  Energy-Aware Writes to Non-Volatile Main Memory

  My passion is to tackle complex computer system problems with creative designs in algorithms and architectures. At a high level

  my research interests include distributed systems

  cloud computing

  and high performance computer architectures. I am especially interested in task and resource management algorithms and the design of advanced virtualization systems. My research is mainly motivated by realistic problems in computer systems and data centers.

  Ron

  Chiang

  Academia Sinica

  AT&T Labs

  Inc.

  Colorado State University

  George Washington University

  University of St. Thomas

  Institute for Information Industry

  \tDevelop J2ME runtime environment for mobile devices\n\tDesign and develop various softwares on mobile devices

  Institute for Information Industry

  University of St. Thomas

  Assistant Professor

  Greater Minneapolis-St. Paul Area

  \tDistributed and heterogeneous computing research

  Colorado State University

  Research Assistant

  \tWork on international research project in conjunction with UC Berkeley to develop new methods for information security and privacy protection

  Academia Sinica

  Research Assistant

  \tCloud computing and virtualization with special focus on storage system

  George Washington University

  Research Intern

  Researching and developing virtualization architectures and management systems

  AT&T Labs

  Inc.