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謝宗佐
Senior Software Engineer
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謝宗佐

Senior Software Engineer
Work on Compiler & ML systems & Kubernetes Skilled in parallel computing, distributed systems Code in C++, C, Golang, python
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Synopsys
國立清華大學
台灣新竹

Professional Background

  • Current status
    Employed
  • Profession
    Software Engineer
  • Fields
    Information Services
  • Work experience
    1-2 years (1-2 years relevant)
  • Management
    None
  • Skills
    C
    C++
    Golang
    Kubernetes
    Docker
    Distributed Systems
    Machine Learning
    Deep Learning
    Tensorflow
    Keras
    Parallel Computing
    CUDA
    Compiler
    Algorithm
    Cloud Computing
  • Languages
    English
    Fluent
  • Highest level of education
    Master

Job search preferences

  • Desired job type
    Full-time
    Interested in working remotely
  • Desired positions
    Software Engineer
  • Desired work locations
    Taipei City, Taiwan
    Hsinchu County, Taiwan
  • Freelance
    Non-freelancer

Work Experience

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Senior Software Engineer

Synopsys
Full-time
Jan 2022 - Present
VCS - verilog compile simulator (C++, C, Compiler Optimization, Python) • Developed and supported debug functionality for SystemVerilog compile simulator • Parallelized design traversal in FSDB dumping, speeding up runtime by 3x with multithreading • Optimized FSDB gate-data loading and reduced 10-60% runtime memory footprint, benefiting customers running hundreds-of-GB designs with tight memory budgets • Initiated a project to migrate STL hash tables to Abseil Swiss tables for a millions-line code base, reducing up to 70% peak memory usage and speeding up hash table queries by 100% • Debugged and resolved urgent customer issues in tight timelines (< 1 day TAT) with limited information, tools, and access to the environment
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Research Assistant

Feb 2020 - Oct 2021
1 yr 9 mos
Voda Scheduler: GPU scheduler for elastic/distributed deep learning workloads in Kubernetes cluster https://github.com/heyfey/vodascheduler (30+ stars) (Golang, Python, Distributed Systems) • Designed and built a GPU scheduler on top of Kubernetes and several open-source projects using microservices architecture • Sped up overall training time by 2.38x and increased cluster utilization by 1.4x with -- State-of-the-art scheduling algorithms with resource elasticity -- Topology-aware scheduling & worker migration to consolidate resources • Designed and implemented the heterogeneous scheduling, auto-scaling, and fault-tolerant mechanisms for the system
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Software Engineer Intern

Jul 2020 - Aug 2020
2 mos
(C, Python, Machine Learning) • Designed algorithm & firmware for real-time embedded system • Introduced machine learning and data visualization to automate issue analysis, saving 90% of human effort

Education

Master of Science (MS)
Computer Science
2019 - 2021
4/4.3 GPA
Description
SCOPE Lab (Scientific Computing On Parallel Environment) - Parallel Computing - Distributed Systems - ML system design
Bachelor of Business Administration (BBA)
Double Major in Law and Computer Science
2014 - 2018