I am currently working in the area of quantum computer architecture. Specifically, my work is in looking for ways to create correct quantum computer programs. These tools and techniques may borrow ideas from classical computing, using domain-specific language features, programming assertions, and lightweight debugging tools.
My PhD dissertation work at Columbia University was in applications of an analog-digital computer architecture in modern scientific computing. In my time as a PhD student, I figured out how to program and run our group’s own prototype analog computer chips. I found a cavernous gap between the scale, precision, and flexibility that modern workloads demand, and the small-scale approximations that analog computers can realistically deliver. So, in my thesis I advocate for using iterative numerical algorithms as an abstraction layer between conventional digital computers and analog accelerators.
My work has caught the attention of DARPA, who funded my team to do a commercialization study through a Small Business Technology Transfer grant. My work has also sparked discussion in the computer architecture research community, who named one of my conference papers one of twelve Top Picks from 2016.
- Yipeng Huang and Margaret Martonosi. 2019. Statistical assertions for validating patterns and finding bugs in quantum programs. In Proceedings of the 46th International Symposium on Computer Architecture (ISCA ’19). [VIDEO] [PDF] [ARXIV] [SLIDES]
- Yipeng Huang and Margaret Martonosi. 2018. QDB: From quantum algorithms towards correct quantum programs. 9th Workshop on Evaluation and Usability of Programming Languages and Tools (PLATEAU 2018). [PDF] [POSTER] [SLIDES]
- Yipeng Huang. 2018. Hybrid Analog-Digital Co-Processing for Scientific Computation. [PDF] [SLIDES]
- Y. Huang, N. Guo, S. Sethumadhavan, M. Seok and Y. Tsividis, “A Case Study in Analog Co-Processing for Solving Stochastic Differential Equations,” 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), Shanghai, China, 2018, pp. 1-5. [PDF]
- Yipeng Huang, Ning Guo, Mingoo Seok, Yannis Tsividis, Kyle Mandli, and Simha Sethumadhavan. 2017. Hybrid analog-digital solution of nonlinear partial differential equations. In Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-50 ’17). ACM, New York, NY, USA, 665-678. (2017 MICRO Top Picks honorable mention) [PDF] [SUMMARY] [POSTER] [SLIDES] [LIGHTNING]
- Y. Huang, N. Guo, M. Seok, Y. Tsividis and S. Sethumadhavan, “Analog Computing in a Modern Context: A Linear Algebra Accelerator Case Study,” in IEEE Micro, vol. 37, no. 3, pp. 30-38, 2017. [PDF]
- Yipeng Huang, Ning Guo, Mingoo Seok, Yannis Tsividis, and Simha Sethumadhavan. 2016. Evaluation of an analog accelerator for linear algebra. In Proceedings of the 43rd International Symposium on Computer Architecture (ISCA ’16). IEEE Press, Piscataway, NJ, USA, 570-582. (2016 MICRO Top Picks) [PDF] [SLIDES]
- N. Guo et al., “Energy-Efficient Hybrid Analog/Digital Approximate Computation in Continuous Time,” in IEEE Journal of Solid-State Circuits, vol. 51, no. 7, pp. 1514-1524, July 2016.
- N. Guo et al., “Continuous-time hybrid computation with programmable nonlinearities,” ESSCIRC Conference 2015 – 41st European Solid-State Circuits Conference (ESSCIRC), Graz, 2015, pp. 279-282.
- J. Weisz, Y. Huang, F. Lier, S. Sethumadhavan and P. Allen, “RoboBench: Towards sustainable robotics system benchmarking,” 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, 2016, pp. 3383-3389. [PDF]
- Simha Sethumadhavan, Adam Waksman, Matthew Suozzo, Yipeng Huang, and Julianna Eum. 2015. Trustworthy hardware from untrusted components. Commun. ACM 58, 9 (August 2015), 60-71.
Department of Computer Science
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