Yiwei Yang (Victor)
Biography
I'm a Junior Computer Science student @ ShanghaiTech
University. I'm honored to be under polished by three system related Professors Foo, Shu and Toast no matter for my research career, my course journey
and high performance cluster competitions.
case class DRAM(tag: String, taste: String, percentage: Int)
val OnCrash = List(
DRAM("HPC Training", "Nice", 40),
DRAM("NVRAM Hooligon", "Damm Hard" 41),
DRAM("Compiler TA", "Thankless", 18),
DRAM("Course Work", "Indifferent", 1))
val CoffeeTime =
for (OnCrash <- Machine if Machine.percentage.delta + Machine.mt19937ar.rand >= 1
&& strcmp(Machine.taste,"So So") >0 && Machine.percentage--) //lazy eval
yield Machine.tag
CoffeeTime.foreach(println)
Skills
Source from Guanzhou Hu
Education
BEing in Computer Science and Engineering
Shanghai, China
September 2018 - July 2022
Industrial Experiences
Serving for HFT team by HPC automated DevOps stack
Shanghai, China
June 2020 - July 2020
- High Frequency Trade Order Book simulation applying Linear.Regression Method.
- Applied salt and jinja to automate scheduling of jobs and assigning affinity of cpu cores in Linux DevOps.
- Applied gobidng of gobpf to try IOVisor stuff.
Leader
September 2019 - Present
Established a team of 16 undergraduate students for HPC related research. Navigated the first
research funding from Inspur and Nvidia. Continually preparing and aiming for the top-tier student
supercomputing competitions, including ASC,ISC
and SC.
- Optimized a parallel quantum computer simulater QuEST by reducing the cache-miss rate and introducing AVX2/AVX512 vectorization for CPU part and adopting NCCL comunication infro for GPU part.
- Compiled and distributed climate simulator CESM on Azure with automated scheduling.
- Optimized a Profiler of MPI alltoallv called collective_profiler by a Nvidia Architect Geoffroy Vallee.
- Added a parallel I/O Middleware for WRF which increase around 30% of the performance.
Research Interests
Computer System (Arch) High
Performance
Computing Symbolic Execution Blockchain &
IoT GPGPU PL Reinforcement Learning
Research Experiences
- Researching Adversarial Sample Detection for Deep Neural Network using foolbox and IBM-ART to improve accuracy of object recognition to prevent impostors from hacking into systems.
- Researching MOVE language in Libra currency source code to protect against Arithmetic Overflow, Timestamp Dependency.
- Understanding the real access mechanism of Memory Mode Optane Memory and XPBuffer by reverse-engineering methods.
- Investigating Order-Dependent Flaky Tests.