In the resource allocation problem in the Distributed Systems under the High Performance Computer, we don't really know which device like disk, NIC (network interface) is more likely to be worn, or not currently on duty which may trigger delaying a while to get the data ready. The current solution is random or round robin scheduling algorithm in avoidance of wearing and dynamic routing for fastest speed. We can utilize the data collected to make it automatic.
Matured system administrator may know the pattern of the parameter to tweak like stride on the distributed File Systems, network MTUs for Infiniband card and the route to fetch the data. Currently, eBPF(extended Berkeley Packets Filter) can store those information like the IO latency on the storage node, network latency over the topology into the time series data. We can use these data to predict which topology and stride and other parameter may be the best way to seek data.
The data is online, and the prediction function can be online reinforce learning. Just like k-arm bandit, the reward can be the function of latency gains and device wearing parameter. The update data can be the real time latency for disks and networks. The information that gives to the RL bots can be where the data locate on disks, which data sought more frequently (DBMS query or random small files) and what frequency the disk make fail.
Benchmarks and evaluation can be the statistical gain of our systems latency and the overall disk wearing after the stress tests.
For pure motivation, I need a Ph.D. for investigating a direction that is worth my life fighting for and the society's values. With the rapid growth of the Chinese economy followed by huge research investment, at least for the past three years in ShanghaiTech, I witnessed extraordinary scientific progress in all disciplines. China has also provided huge markets to fast deploy the research results and companies start to be willing to devote higher salaries and equipment for new grads to dig into their research fields. However, most professor in our school only takes care of short-term profits and put many efforts into applications of established ideas, which things solely get one direction worse in other institutes. Plus, no profitable company is founded on tech infrastructure as Nvidia, Intel and Xilinx do but exploiting the unsophisticated public's time like Tencent and ByteDance. That accounts for the U.S.A. is still the origin of innovation today. In China, the general public's pure pursuit for better technology downturns to self-imposed comfort based on the current circumstance. But, I'm not and from the bottom of my heart, want to use technology to change.
I recently published a paper on the adversarial sample in AI security scenario on ISSTA21 as the fourth author under the supervision of Prof. Fu Song. I helped the first author Ph.D. candidate Zhe Zhao run most experiments during my Freshman summer. It innovatively utilized the fact label change rate through model mutation testing to distinguish adversarial examples and put them on defend the data that use this technique, which we called Attack as Defense. I got to know how software engineering testing works on artificial intelligence and could apply to any other places like language spec on smart contracts, operating system‘s concurrency, and computer architecture's semantics. That's my two other Work-In-Progress work mainly focus on, to use Z3 solver on verifying the possible timestamp attack and arithmetic overflow on Diem move language. During my weekly seminar at System and Software Security Lab for two years, I grabbed ideas like Decision Procedures, basically, the originality/application of SMT solver as the combination of logic and program, fuzzing techniques, and Capture The Flags Surroundings - a security competition.
From my Sophomore year on, my main focus turns into industrial needs practice. GeekPie_HPC is a place I devote time to. We just obtain second place at SC21-SCC. I would say I put the obscure system knowledge into production on high-performance heterogeneous systems. For example, I got how the Linux system called flock work in class, but not until I found it messy once linking on GPFS with un-updated data drag me into this semantic deeper, I resolved it by fsync to manually force synchronize. I knew Cuda only as a library importer using Pytorch auto-gradient that for sure run on GPU, not until I compare different compiler hint with different HPC algorithm and MPI scatter/reduce and alltoallv takes me to figure out how data transmit on GPU. My school establishes a long-term connection to Jump Trading by us winning the super clustering competition that the recruiter gets to know that our students are unique to problem-solving with the right tools. My experience at Jump Trading in sophomore summer let me dig into the more cutting-edge technology eBPF and Intel Mesh Micro Architecture. However, the main focus of industrial is quite different. I mostly applied for the kernel dynamic inspection work on the distributed filesystem in terms of different lease users and apply the core affinity strategy considering core to NUMA, DDR, NIC, and GPU latency. From my perception through my ex-colleague, more production level engineers usually have Bachelor Degree only and are cultivated by the company like my mentor, but the real secret big thing is usually brought by Ph.D. like the author of eBPF or reverse-engineering work on intel processors.
For this summer, I remotely joined Darko Marinov's as REU(research experience for undergrads) and worked with a Peking University classmate Ruidong Zhu for testing order-dependent tests. I started a brand-new direction as pure software testing on order-dependent JUnit tests. Flakiness means tests may fail or pass for different rounds. This could be triggered by some order-dependent values which could be identified on Darko's iDFlaky tool automatically run on Azure. For testing, their previous work explains the cleaner, polluters, and victims of specific variables on specific values. Their latest work submitted for ICSE21 is to introduce Non-idempotent tests that could be identified by running methods one after one in isolated methods/class/entire suite to see whether they may be flaky. We run a dynamic taint analysis tool called PraDet on all the runnable tests on three of their latest test suites and report. We are currently modifying a more advanced tool based on these limitations. During the process. I'm intrigued by the passion of my mentor Wing Lam and Darko's energy in thoughts in contrast to his lazy lying posture.
For choosing UMich, I'm captivated by a school that chose potential people that are intrinsically apt with engineering problem-solving skills and cultivate them into world-class researchers like Baris Kasikci. The recently published paper "Rethinking File Mapping for Persistent Memory" on FAST21 is really amazing. The authors propose to use hash for File Mapping. an example is given in the text, PMem is divided into a file data region and metadata region, if the logical address to be mapped is <inum=1, iblk=21>, the offset of this logical block in the hash is i, then the physical block address corresponding to this logical block is ( file data region start address + i*4KB). There is 5+ paper every year from Baris. For these world-class research opportunities, the CS department of UMich is especially attractive to me. It would be a privilege to study under the guidance of its remarkable faculty during "A New Golden Age for Computer Architecture".
I have enjoyed being able to apply what I learned in classes such as computer architecture and the principle of the compiler to my research. On the other hand, I have also cultivated a broad interest in other areas, such as Reinforce Learning, as a source of inspiration. I seek different kinds of creativity in engineering and in the beauty of itself when it was realized. It is this creative will that I wish to pursue in UMich's Ph.D. program and afterward as a researcher in the industry. My learning experience under the guidance of my advisor convinced me not only of the potential of research but also of the value of teaching. I have also enjoyed working as an undergraduate teaching assistant for the compiler. Through my course studies, I expect to become and will work hard to be a productive researcher and teacher.
First of all, my previous experience makes me an open-minded person with high motivation that does not take the current circumstances for granted. I think that kind of momentum and curiosity is cultivated through my travel and experience. As for the social practices, for the summer of Sophomore, 20 other students and I come to PingTang, the place installed with a Five-hundred-meter Aperture Spherical Telescope. We investigated how this externality affects the locals' tourism from the first year's pouring of capital to the second year's over-saturated and how it changed with the downturn of the Chinese economy. China's investment of Infrastructure is fundamental to every public in the rural area, and socialism is taking effect with the targeted poverty alleviation in this Xi's time. 800 RMB per year per family is the definition of the poor and until 2020 if he's still under this line, he has disabled member or unwillingness to labor. However, criticism is cast on the push of every man to engage in the smallholder economy like strawberries that do not match the local environment. I solo visit HK during the protest, Singapore, Malaysia, Thailand, India, and Nepal within 12 days. I witnessed the big countries' hegemony and small country esteem. I witnessed the deep inequality of poverty in this world and the importance of establishing the network/highway infrastructure.
The open mind takes me naturally into a diverse environment. My previous employer, Jump Trading is a place that embraces diversity. I first come to realize that in a tiny office, there exists multiple races, LGBTQ+, multiple languages as a native language, and multiple religions. For communicating more fluently without barriers, all we did is to respect with no discrimination. The colleague who worked with me is an MtF(Male to Female), besides calling 'her', talking off sex mutual stuff and no man's joke. My mentor is born in Malaysia and his mother is from England and his father is from Hong Kong. So he's quite familiar with Cantonese words. From a technical perspective, the people who graduated from French Schools focus more on mathematical proof as well as intuition while those from American Schools care more about implementation and effectiveness. We are valuing every people from different backgrounds which I'm tuned a while for it since I'm situated in a single race country with a single religion. Every year, there are 3 top-tier competitions for super-cluster competition and I'm the lead for the team to compete with prestigious universities like UCSD, UIUC, and Gatech. Our team GeekPie_HPC has recruited 2 females out of 6 for daily training and eventual competition. We highly recommend female computer science students to join in such a low female density department.
My research taste and delight come from the demand of my curiosity. Many dummy things happen when choosing the courses and taking exams, I get accustomed to getting the hardest course that gives me the challenge of pressure. Once I'm determined to do something, I would focus on the point until it's figuring out or give up it because I knew the stuff does not fit me. The overall process of college for me is a time of testing failures. The projects and exams are similar to a I knew that I have many shortages, but it didn't bother my desperation to solve hardest open questions.
Jung making-connection Letter
I’m CS Undergrad from ShanghaiTech specializing in general systems. I grabbed most of my practical skills by attending GeekPie HPC. I spent some time working on eBPF and intel processor micro arch at Jump Trading Shanghai (which has proven to be engineers' efforts talking with other guys but get me into the micro arch world). During summer 2022, I worked on Java Flaky Testing with Darko Marinov from UIUC. During my time at Chundong's lab, we discussed a lot on your paper of study on failure tolerance, memory order bugs, and performance on Optane persistent memory. I referred to your paper for grabbing a general knowledge of how to tune performance on Optane Memory. I think I could put energy into them if I had the opportunity to join your team. Sincerely, would you recruit Ph.D. or masters this year?