Bojie Li

(This article is a compilation of the author’s speech at Peking University on December 12, 2022, first converting the conference recording into a draft using iFlytek’s voice recognition, then polishing it with GPT-4, correcting errors in voice recognition, and finally manually adding some new thoughts)

• Part 1: The New Golden Age of Computer Networks (Part 1): Data Centers
• Part 2: The New Golden Age of Computer Networks (Part 2): Wide Area Networks

Wireless networks are a very broad field, corresponding to Huawei’s two major product lines, one is wireless, and the other is consumer BG. Wireless mainly refers to the familiar 5G and Wi-Fi, while consumer BG includes various smart terminals including mobile phones.

At the beginning of the last chapter on wide area networks, we mentioned that the current transmission protocols do not fully utilize the bandwidth of wireless networks and wide area networks, resulting in many applications actually unable to experience the hundreds of Mbps high bandwidth claimed by 5G and Wi-Fi. This is what we often call the “last mile” problem. As the performance of wireless networks becomes closer and closer to wired networks, some optimizations originally applicable to data centers will apply to wireless networks. Previously, when we talked about distributed systems, we thought of data centers, but now there are so many terminal devices and smart home devices at home, which also form a distributed system. In the future, a family may be a mini data center.

(This article is a compilation of my speech at Peking University on December 12, 2022, first converted into a draft using iFlytek’s voice recognition technology, then polished and corrected using GPT-4, and finally supplemented with some new thoughts manually)

• Part One: The New Golden Age of Computer Networks (I): Data Centers

Wide Area Networks (WANs) mainly fall into two categories of communication modes, one is end-cloud communication, and the other is inter-cloud communication. Let’s start with end-cloud.

End-Cloud Networks

When we generally mention WANs, we assume they are uncontrollable, as the network equipment of the operators is not under our control, and there are a large number of other users accessing concurrently, making it difficult to achieve determinism. But many of today’s applications require a certain degree of determinism, such as video conferencing, online games, where users will feel lag if the delay is too high. How to reconcile this contradiction? That’s our topic today.

As we mentioned in the previous chapter on data center networks, the bandwidth actually perceived by applications is much less than the physical bandwidth, hence there is room for optimization. We know that the theoretical bandwidth of both 5G and Wi-Fi is hundreds of Mbps or even Gbps, and many home broadband bandwidths are also hundreds of Mbps or even reaching gigabit levels. In theory, 100 MB of data can be transmitted in one or two seconds. But how many times have we downloaded an app from the app store and it finished in one or two seconds for a 100 MB app? Another example, a compressed 4K HD video only requires a transmission speed of 15~40 Mbps, which sounds far from reaching the theoretical limit of bandwidth, but how many network environments can smoothly watch 4K HD videos? This is partly a problem with the end-side wireless network and partly a problem with the WAN. There is still a long way to go to make good use of the theoretical bandwidth.

When I was interning at Microsoft, the Chinese restaurant on the second floor of the Microsoft Building was called “Cloud + Client”, and the backdrop at the sky garden on the 12th floor also read cloud first, mobile first. Data centers and smart terminals were indeed the two hottest fields from 2010 to 2020. Unfortunately, Microsoft’s mobile end never took off. Huawei, on the other hand, has strong capabilities on both the end and cloud sides, giving it a unique advantage in end-cloud collaborative optimization.

(This article is organized based on the speech I delivered at Peking University on December 12, 2022, first converting the conference recording into a draft using iFlytek’s speech recognition, then polishing it with GPT-4 to correct errors from voice recognition, and finally manually adding some new thoughts)

I am very grateful to Professor Huang Qun and Professor Xu Chenren for the invitation, and it is an honor to come to Peking University to give a guest lecture for their computer networking course. I heard that you are all the best students at Peking University, and I could only dream of attending Peking University in my days. It is truly an honor to have the opportunity to share with you some of the latest developments in the academic and industrial fields of computer networking today.

Turing Award winner David Patterson gave a very famous speech in 2019 called “A New Golden Age for Computer Architecture”, which talked about the end of Moore’s Law for general-purpose processors and the historic opportunity for the rise of Domain-Specific Architectures (DSA). What I am going to talk about today is that computer networking has also entered a new golden age.

The computer networks we come into contact with daily mainly consist of three parts: wireless networks, wide area networks, and data center networks. They provide the communication foundation for a smart world of interconnected things.

Among them, the terminal devices of wireless networks include mobile phones, PCs, watches, smart homes, smart cars, and various other devices. These devices usually access the network through wireless means (such as Wi-Fi or 5G). After passing through 5G base stations and Wi-Fi hotspots, the devices will enter the wide area network. There are also some CDN servers in the wide area network, which belong to edge data centers. Next, the devices will enter the data center network. In the data center network, there are many different types of devices, such as gateways, servers, etc.

Today, I will introduce you to data center networks, wide area networks, and terminal wireless networks. First, let’s look at data center networks. The biggest change in data center networks is the evolution from simple networks designed for simple web services to networks designed for large-scale heterogeneous parallel computing, performing tasks traditionally handled by supercomputers, such as AI, big data, and high-performance computing.

** (Article from the WeChat public account of the Intelligent Manufacturing Society, original link, many thanks to the Intelligent Manufacturing Society for their excellent questions and editing) **

What impact will AI ultimately have on the technology and life of human society?

With the release of GPT4, the performance of large model AI has once again refreshed the public’s imagination. The content produced by AIGC is becoming more realistic and refined. With the continuous deepening of data cleaning and training, AI’s understanding of natural language has also shown great progress. From passively accepting data “feeding” to actively asking questions to the world, perhaps, the “artificial intelligence life” in science fiction is no longer far away from us.

Anxiety is inevitable, and “AI unemployment” seems to be really happening in some industries. On May 18, 2023, local time, BT, the largest telecom operator in the UK, said it would cut 40,000 to 55,000 jobs between 2028 and 2030. The layoffs will include BT’s direct employees and third-party employees, reducing the company’s total number of employees by 31-42%. Currently, BT has about 130,000 employees.

BT’s boss Philip Jansen publicly stated that after completing fiber optic deployment, digitizing work methods, adopting artificial intelligence (AI), and simplifying its structure, it will rely on fewer labor and significantly reduced cost base, “the new BT Group will be a leaner enterprise with a brighter future”. Looking back at home, some Internet technology companies have also shown related trends, especially the art outsourcing positions of game companies, which can be described as “disaster areas”.

Speaking of this issue, Li Bojie, assistant scientist at Huawei 2012 Lab, said that some of the public’s anxieties have been magnified by the media. AI technology is not a flood beast that replaces humans, but rather, it liberates productivity and shapes more new jobs. “For example, if we look at the past industrial revolution, people who used to do farming now have to use machines. The education they need, as well as the changes in society, economy, and people’s lifestyle, are all very big.”

Li Bojie believes that after AI technology becomes popular and becomes a new production tool, more industries and occupations will be generated in response. “For example, after the computer, there is no need for a copyist to copy things hard, right? AI is the same, some industries directly involve people, it can’t replace, like the service industry, right? But some things that follow the rules and do fixed patterns, AI can simplify a lot of labor.”

As a researcher of data center network technology closely related to AI, Li Bojie has put forward many views and thoughts on AI. Below is the conversation record of Xiao Zhi, the main writer of the Intelligent Manufacturing Society, and Li Bojie:

This is an old article of mine from 5 years ago. It was a winter night in early 2018 when I set up a large pot by myself in the Thirteen Tombs and sent a small part of human knowledge to Sirius, 8.6 light-years away. The story behind this can be found here. Today, what we are concerned with is that sending messages to potential extraterrestrial civilizations obviously requires making them recognize that the message is sent by an intelligent life form, and also making them understand it.

A very basic question is, how do you prove your level of intelligence in the message? In other words, if I were an intelligent life form monitoring cosmic signals, how would I determine whether a bunch of signals contains intelligence? Since intelligence is not a matter of having or not having, but rather more or less, how do we measure the degree of intelligence contained in these signals? I think my thoughts from 5 years ago are still interesting, so I’m organizing and posting them.

The message is just a string. Imagine we could intercept all communications from aliens and concatenate them into a long message. How much intelligence does it contain? This is not an easy question to answer.

Current technology generally tries to decode the message and then see if it expresses basic information from sciences such as mathematics, physics, astronomy, logic, etc. The Arecibo message from 1974 was encoded in this way, hoping to attract the attention of extraterrestrial civilizations. I tried to find a purely computational method to measure the level of intelligence contained in the message.

This WeChat Moment from yesterday sparked a lot of discussion both inside and outside the company, and many people reached out to me.

I considered it from two perspectives: innovation and commercialization.

Long read warning: Part two of the “Five Years of PhD at MSRA” series, about 13,000 words, to be continued…

• Part One: From Novice to My First SIGCOMM Paper

KV-Direct, published at SOSP 2017, was my second paper (as first author). Since the first SIGCOMM paper ClickNP was done with Bo Tan guiding me step by step, KV-Direct was also the first paper I led on my own.

What to Do After SIGCOMM

After submitting the SIGCOMM paper, Bo Tan said that for the next project, I needed to come up with the direction on my own.

Compiler or Application?

We were well aware that ClickNP still had many issues, with the current support for compilation optimization being too simple. We hoped to enhance the compiler’s reliability from the perspective of programming languages. At the same time, we used ClickNP as a common platform for network research within our group to incubate more research ideas.

Naturally, I explored along two directions, one was to extend ClickNP to make it easier to program and more efficient; the other was to use the ClickNP platform to develop new types of network functions to accelerate various middlewares in the network. At that time, we were exploring many middlewares in parallel, such as encryption/decryption, machine learning, message queues, layer 7 (HTTP) load balancers, key-value stores, all of which could be accelerated with FPGAs.

To improve the programmability of ClickNP, I started looking for good talents from the school to join the MSRA internship. Yi Li was interested in programming languages and formal methods during his undergraduate studies. He was the first student I recommended to intern at MSRA. At the start of the spring semester, Yi Li came to MSRA for his internship, coinciding with the completion of his undergraduate thesis. He proposed several key optimizations for the ClickNP system, added some syntax to simplify programming, and corrected some awkward syntax.

However, due to the workload, we did not do a major overhaul of the compilation framework, still using simple syntax-directed translation without using professional compiler frameworks like clang, nor intermediate languages. Therefore, each time a new compilation optimization was added, it seemed rather ad-hoc.

Encountering various strange issues with OpenCL, I had the idea of creating a high-level synthesis (HLS) tool myself, generating Verilog directly from OpenCL. My idea was simple: for application scenarios in the networking domain, what we do is to unroll all loops in a piece of C code into a large block of combinational logic. By inserting registers at appropriate positions, it could become a pipeline with extremely high throughput, capable of processing an input every clock cycle. If the code accesses global states, then such loop dependencies determine the maximum number of registers on the dependency path, which is the upper limit of the clock frequency.

However, Bo Tan disagreed with my idea of creating an HLS tool ourselves, because we were not professional FPGA researchers. Such work lacked innovation, more about filling the “gaps” of existing HLS tools, a engineering problem, difficult to publish top-tier papers in either FPGA or networking fields.

Due to frequent issues with FPGA card programming, I ended up plugging and unplugging FPGA cards in the server room every day, sometimes debugging on-site. Thus, like my undergraduate days in the minor academy’s server room, I often spent hours in the server room, enduring the cold air and noise over 80 decibels.

Long article warning: The first in the “Five Years of PhD at MSRA” series, about 12,000 words, to be continued…

On July 31, 2021, at the ACM Turing Conference in China, I was standing on the podium waiting for the ACM China Outstanding Doctoral Dissertation Award. I didn’t expect that the person who came up to present the award to me was President Bao, and my legs involuntarily trembled a bit. This was the only time I had seen President Bao up close. President Bao happily said that seeing one of us from USTC among the award winners shows that USTC can also cultivate masters. He hoped that we could become masters in the future, serve our motherland, and return to our alma mater.

The host of the award ceremony, Professor Liu Yunhao, asked us to talk about the title of our doctoral dissertation and our advisors. I blurted out, “High-Performance Data Center Systems Based on Programmable Network Cards“, my advisors are Professor Chen Enhong from USTC and Dr. Zhang Lintao from Microsoft, and I would like to give special thanks to Dr. Tan Kun from Huawei. I can clearly remember the title of my doctoral dissertation, it’s hanging on my homepage. In the company, people often send me private messages asking if I am the author of a certain paper. I would shyly say, yes…

Many people may think that I am the kind of PhD student who is solely focused on studying, but my PhD life is actually much more interesting than many people imagine, truly embodying the MSRA (Microsoft Research Asia) motto “Work hard, play harder“.

Research Novice

Joint Training

MSRA (Microsoft Research Asia) has joint PhD training programs with many universities in China. Among them, the joint training program with USTC has been ongoing for many years. In the second semester of my junior year, MSRA interviewed dozens of candidates at our school, selected about a dozen students for summer internships and a year-long internship in their senior year, and after the summer internship, about 7 students were confirmed to become joint training PhDs. These joint training PhDs will complete their first year of master’s and doctoral courses at USTC, and the next four years will be spent on academic research at MSRA in Beijing, finally obtaining a PhD degree from USTC.

The requirements for MSRA to select joint training PhDs are the so-called “three good” students: good at math, good at programming, and good attitude. This rule is said to have been set by the former dean, Dr. Shen Xiangyang. Because I spent all day tinkering with various Linux network services in the Youth Class College computer room and LUG activity room during my undergraduate studies, I didn’t study very well, and naturally my grades weren’t very good. My GPA was only 3.4 (out of 4.3), and I even failed Calculus II. The interviewer asked me at the time why my math grades were so poor. Probably because I had won awards in programming competitions (NOI) in high school, and my resume had many network service projects I worked on at LUG, I was surprisingly admitted to the joint training PhD program. The GPAs of other students admitted to the joint training program were at least 3.7, and most of them were top students with 3.8 or above.

I found a VCD disc from the pile of old papers, which was given to me by Shijiazhuang TV station in 2004. After restoration and transcoding, the interview program “Superstar Li Bojie - Remembering the Hua Luogeng Gold Cup Gold Medalist” broadcasted 19 years ago finally sees the light of day again.

From this 13 and a half minute video, you can see how fat I was back then :) The sports question that was publicly revealed starts at 11:25 in the video :)

Time: May 1, 2023, 10:58

Location: Cui Ping Shan Hotel, Hebei

Transportation Information: Cui Ping Shan Hotel is located at No. 1 Yingbin Road, Luquan District, Shijiazhuang City, Hebei Province.

• As Cui Ping Shan Hotel is located in the western suburbs and is not accessible by subway, public transportation is inconvenient. It is recommended to take a taxi.
• High-speed rail:
  • By car: The nearest route from Shijiazhuang High-speed Rail Station is 16 kilometers, and the elevated route is 22 kilometers. It takes about 35 minutes by car without traffic.
  • Public transportation: You can take bus 320 / air 320 directly (need to walk 1.3 kilometers), which takes 1 hour and 20 minutes; or take subway line 3 to subway line 1 to tourist bus 5, which takes 1 hour and 10 minutes.
  • The taxi queue at Shijiazhuang High-speed Rail Station is very long after 22:00. If you arrive late, it is recommended to contact us in advance for pick-up.
• Airplane:
  • By car: It is 53 kilometers from Shijiazhuang Zhengding International Airport, and it takes about 50 minutes by car without traffic.
  • Public transportation: From Zhengding Airport, you can take Airport Bus Line 1 (one bus per hour) to Subway Line 1 to Tourist Bus 5, which takes 2 hours and 10 minutes.
  • It is inconvenient to take a taxi at Zhengding Airport at night. If you arrive late, it is recommended to contact us in advance for pick-up.
• As the wedding officially begins at 10:58, it is recommended to arrive in Shijiazhuang on April 30. Those departing from Beijing who are short on time can also consider taking the early high-speed rail on May 1 (5 departures from 06:26 to 08:34).

Accommodation Information:

• Try to arrange to stay in Building 6 and Building 9 of Cui Ping Shan Hotel, Hebei, where rooms have been reserved. If there are special circumstances, we will arrange nearby hotels.
• Breakfast is expected to be in Building 6, from 7:00 to 10:00. Bridesmaids, groomsmen, and staff need to leave early and will not have time for breakfast, so a simple meal will be arranged in Buildings 6 and 9.
• The distance between Building 6 and Building 9 is 560 meters, and it takes 8 minutes to walk.