Tag Archives: Dissertation

Jie Graduates. Congrats Dr. You!

August 5, 2022 Mosharaf

Jie (Jimmy) has recently become my third PhD student to graduate with a dissertation titled “Toward Practical Application-Aware Big Data Systems.” Over the course of his PhD, Jimmy ended up contributing to most of the major projects of our group over the years, and we will miss him going forward. He’s joining Meta.

Jimmy officially started his PhD at Michigan in Fall 2016, but he started working with me from Summer 2017. He started working on one of the first projects of SymbioticLab on geo-distributed analytics that had taken many names over the years (Gaia/Terra/System H). While the core project didn’t go as expected, it created tools and artifacts that helped other projects published in SPAA and NSDI that Jimmy contributed to. After that Jimmy learned that sometimes its better to come up with your idea, and he successfully led end-to-end the Kayak project that provided a middle-ground between KV- and RPC-based systems. This was done in collaboration with Xin and his group. After moving from high-latency to low-latency networks, Jimmy’s final project moved in another very different direction. In Zeus, Jimmy and Jae-Won collaborated on understanding and optimizing the energy consumption of DNN training. I think Zeus is the best of his works and will have a lasting impact. While it was stressful as an advisor to see him change course so many times in a PhD, it was also fun to see him eventually find his footing on his own terms.

Jimmy is very inquisitive, which led to him exploring many different things during his PhD. He is also very good at taking feedback and improving himself, which he’s clearly demonstrated over the past five years. I’m sure he’ll ask many questions and explore many new things in the next chapter(s) of his career.

Peifeng has Phinished. Congrats Dr. Yu!

June 2, 2022 Mosharaf

Peifeng just became my second student to finish PhD a few days ago after successfully defending his dissertation “Application-Aware Scheduling in Deep Learning Software Stacks.” This will be a big loss for the SymbioticLab as we will miss his presence and deep technical insights. Peifeng is joining Google to continue working on resource management systems for AI/ML.

Peifeng officially started his PhD in Fall 2017, but he started working with me on and off from the Fall before when he took EECS 582 with me as a master’s student at UM. Peifeng and his friend, Linh, were working on a term project on video captioning for that course, but Peifeng was interested into better designing systems for AI/ML instead of simply applying existing ML techniques to different use cases. Although I did not know anything about systems for AI/ML, Peifeng pulled me into this world. Since then, Peifeng has worked on several groundbreaking projects, including Salus and Fluid; Orloj, an even more exciting project is in the pipeline to be published. Salus was the first software GPU sharing solution that provided significantly higher utilization than NVIDIA MPS; Fluid was the first leverage the collective nature of jobs in hyperparameter tuning to improve GPU- and cluster-level utilizations. Orloj is the first inference system to provide predictable performance for dynamic DNNs while maintaining the best-in-class performance for traditional static DNNs. I enjoyed this journey thoroughly, learned a lot in the process, and am really proud to be called his advisor.

Peifeng is one of the best (ML) systems developers I have ever seen (and I have seen many luminaries over years). He cares more about doing his work than hyping them up. He is also unbothered by the publications rat race to the point of causing advisor anxiety.

I have no doubt he will be extremely successful in whatever he sets his mind to.

Juncheng Levels Up. Congrats Dr. Gu!

August 27, 2021 Mosharaf

My first Ph.D. student Juncheng Gu graduated earlier this month after successfully defending his dissertation titled “Efficient Resource Management for Deep Learning Clusters.” This is a bittersweet moment. While I am extremely proud of everything he has done, I will miss having him around. I do know that a bigger stage awaits him; Juncheng is joining the ByteDance AI Lab to build practical systems for AI and machine learning!

Juncheng started his Ph.D. in the Fall of 2015 right before I started in Michigan. I joined his then advisor Kang Shin to co-advise him as he started working on a pre-cursor to Infiniswap as a term project for the EECS 582 course I was teaching. Since then, Juncheng worked on many projects that ranged from hardware, systems, and machine learning/computer vision with varying levels of luck and success, but they were all meaningful works. I consider him a generalist in his research taste. Infiniswap and Tiresias stand out the most among his projects. Infiniswap heralded the rise of many followups we see today on the topic of memory disaggregation. It was the first of its kind and introduced many around the world to this new area of research. Tiresias was one of the earliest works on GPU cluster management and certainly the first that did not require any prior knowledge about deep learning jobs’ characteristics to effectively allocate GPUs for them and to schedule them. To this day, it is the best of its kind for distributed deep learning training. I am honored to have had the opportunity to advise Juncheng.

Juncheng is a great researcher, but he is an even better person. He is very down-to-earth and tries his best to help others out whenever possible. He also understates and underestimates what he can do and has achieved, often to a fault.

I wish him a fruitful career and a prosperous life!