Here is my gang of the best and brightest students I work(ed) with.
Alumni of our Group
- Hyeran Jeon, Phd, Asst. Professor, San Jose State University, May 2015
- Daniel Wong, Phd, Asst. Professor, Univ of California, Riverside, May 2015
- Waleed Dweik, Phd, Asst. Professor, Univ of Jordan, Amman, Jan 2015
- Frankie Romero, Undergraduate Research Student, Graduated with BS in May 2015. Currently PhD Student at Stanford Univ.
- Justin Kuang, Undergraduate Research Student, Graduated with BS in May 2014. Currently MS Student at Stanford Univ.
- Melina Demertzi, MS, Oracle, May 2013.
- Bardia Zandian, PhD, Senior Engieer, Qualcomm, May 2013
- Ricardo Rojas, Undergraduate Research Student, Graduated with BS in May 2012. Currently PhD Student at Stanford Univ.
- Jinho Suh, Graduated with a PhD in Jan 2012 (co-advised with Michel Dubois). First employment Intel.
- Sabyasachi Ghosh, Graduated with an MS in May 2011. First employment at Riverbed Technologies.
- Thomas Punihole, Undergraduate Research Student, Graduated with BS in May 2010. MS Student at USC.
- Kimish Patel, Graduated with a PhD in August 2010 (co-advised with Massoud Pedram). First employment at NVidia
- Yi Wang, Graduated with a PhD in August 2010. (co-advised with Bhaskar Krishnamachari) First employment Juniper Networks.
- Hua Liu, Graduated with a PhD in Aug 2010 (advised primarily by Bhaskar Krishnamachari).
- Sukhun Kang, Graduated with an MS in May 2010. First employment at Samsung LSI Technologies.
- Prof. Won Wo Ro, Professor, Yonsei University, Korea, May 2014-Aug 2015, Sabbatical at USC.
- Sangpeel Lee, Visiting Phd Student from Yonsei University, June 2014-Aug 2015.
- Kuensoo Kim, Visiting Phd Student from Yonsei University, June 2014-Aug 2015.
- Myung Kuk Yoon Visiting Phd Student from Yonsei University, Jan 2015-Aug 2015.
My Research Agenda
The decade of 80s has been hailed as the era of supercomputing in a room. 90s is the era of supercomputing on a desktop and finally the current decade is the era of supercomputing on a laptop. The dramatic reduction in computer form factor is a cumulative result of innovations at all levels of computer design; from process technologies to architectural innovations. There are, however, signs that the rate of process technology scaling is slowing and process variations are becoming dominant while at the same time architectural innovations are facing stringent constraints on power consumption. I consider these challenges as new research opportunities. Hence, my research will focus on bringing the power of supercomputing into a pocket within the next decade. In order to achieve this goal extreme system integration is the key first step. Based on my industrial research experience I plan to pursue 3D stacking as the technology enabler for such system integration. In particular, I will explore the challenges and opportunities in stacking heterogeneous system components such as graphics, network processors, flash memory and even I/O components such as solid state disk drives in a single 3D stack. 3D stacking allows disparate silicon technologies to be combined in a die stack, while dramatically reducing the latency between components.These advantages open up new design tradeoffs that were infeasible earlier. For instance, stacking memory on GPU can reduce the need for expensive GDDR memory since 3D DRAM exceeds the bandwidth capabilities of GDDR. My current research on 3D stacking gave me insights into the power, performance, thermal and design issues for 3D stacking. I plan to use some of these insights to expand my research agenda to explore more aggressive 3D stacking options.
Once the power of supercomputing is available in a users pocket the logical next step is to harness the collective compute and communication power of billions of mobile devices to create new usage models in future, such as real time traffic monitoring and social networking. I will research how to allow mobile devices to proactively interact and share the knowledge of their surroundings without compromising privacy and security. For instance, a mobile device user can request for a recommendation of a restaurant with the least waiting times within the vicinity. Users in nearby restaurants can provide this information in real time, provided the information does not compromise the privacy and the provider has an incentive for providing the information. There are challenges both at the hardware and software level for these new usage models to work, which will be the focus of my mobile platform research.