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De 4 a 6 años
6-10 años
10-15 años
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Taipei City, Taiwan
Avatar of 吳俊瑩.
Avatar of 吳俊瑩.
Past
Industrial Engineer @鴻海精密工業股份有限公司
2019 ~ 2023
Data Analyst 數據分析師 / Data Scientist 資料科學家
En un mes
據 ·思緒縝密、規劃能力強,領導團隊朝目標推進 ·積極主動、學習能力佳,持續吸收新知識 [email protected] 技能 Skills • Python • R • Power BI • MySQL • SAP • SAS • Pandas • Numpy • MatplotlibScikit-learn • Seaborn • TOEIC 705 工作經歷 Work Experience 鴻海 Foxconn Industrial Internet, IE工程師/AI專案分析師 , Feb 2019 ~ Jun工業4.0、 數位轉型專案推導 (70%): 協助工
python
R
SAP
Desempleado
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
國立臺北大學 National Taipei University
經濟學
Avatar of 梁賦康 (Foo-Hong, Leong).
Avatar of 梁賦康 (Foo-Hong, Leong).
Product Manager @東元電機股份有限公司 (TECO Electric & Machinery Co. Ltd.)
2023 ~ 2023
Data Scientist, Data Analyst, Machine Learning Engineer
En un mes
梁賦康 (Foo-Hong, Leong) Taoyuan City, Taiwan Email: [email protected] Tel:Skills • Languages: Python • DataBases: MySQL, SQLite • Infrastructure tools: Github • Machine learning libraries: TensorFlow, Keras, and Scikit-learn • Data visualization tools: Power BI, Seaborn and Matplotlib • Deployment: Streamlit Summary I have been working in Motor Manufacturing Industry for 8 years. My first programming was going to my Bachelor's degree, C++ was the first program I learned. Then I started to learn Python in 2018 at TEDU and my first project was the Stock Trend Prediction by CNN. I kept
Python
Power BI
Data Analytics
Empleado
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
6-10 años
國立成功大學 National Cheng Kung University
Mechanical Engineering

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En el plazo de dos meses
Senior Software Engineer
Logo of Synopsys.
Synopsys
2022 ~ Presente
台灣新竹
Professional Background
Situación actual
Empleado
Progreso en la búsqueda de empleo
Professions
Software Engineer
Fields of Employment
Information Services
Experiencia laboral
1-2 años
Management
Ninguno
Habilidades
C
C++
Golang
Kubernetes
Docker
Distributed Systems
Machine Learning
Deep Learning
Tensorflow
Keras
Parallel Computing
CUDA
Compiler
Algorithm
Cloud Computing
Idiomas
English
Fluido
Job search preferences
Posición
Software Engineer
Tipo de trabajo
A tiempo completo
Ubicación
台灣台北, 台灣新竹
A distancia
Interesado en trabajar a distancia
Freelance
No.
Educación
Escuela
國立清華大學
Mayor
Computer Science
Imprimir

Experience

Synopsys Inc.

Jan. 2022 - Present

Senior Software Engineer

VCS - Verilog Compile Simulator

C++, C, Compiler Optimization, Parallel Computing, Python

  • Developed and supported debug functionality for SystemVerilog compile simulator
  • Parallelized design traversal in FSDB waveform 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

MediaTek Inc.

July 2020 - Aug. 2020

Software Engineer Intern

C, Python, Machine Learning

  • Designed memory management algorithm & firmware for real-time embedded system
  • Introduced machine learning and data visualization to automate issue analysis, saving 90% of human effort

Projects

Voda Scheduler

Feb. 2021 - Nov. 2022

 https://github.com/heyfey/vodascheduler  

(30+ stars)

GPU scheduler for elastic/distributed deep learning workloads in Kubernetes cluster 

Golang, Python, Distributed Systems

  • Architected and built a GPU scheduler using microservices architecture on top of Kubernetes and various open-source projects
  • 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 heterogeneous scheduling, auto-scaling, and fault-tolerant mechanisms for the system

Publication

Tsung-Tso Hsieh, Che-Rung Lee: "Voda: A GPU Scheduling Platform for Elastic Deep Learning in Kubernetes Clusters", in IEEE International Conference on Cloud Engineering (IC2E), 2023

Education

National Tsing Hua University

Computer Science, M.S.

SCOPE Lab (Scientific Computing On Parallel Environment)

2019 - 2021

National Tsing Hua University

Double Major in Law and Computer Science, B.S.

2014 - 2018

Resume
Perfil

Experience

Synopsys Inc.

Jan. 2022 - Present

Senior Software Engineer

VCS - Verilog Compile Simulator

C++, C, Compiler Optimization, Parallel Computing, Python

  • Developed and supported debug functionality for SystemVerilog compile simulator
  • Parallelized design traversal in FSDB waveform 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

MediaTek Inc.

July 2020 - Aug. 2020

Software Engineer Intern

C, Python, Machine Learning

  • Designed memory management algorithm & firmware for real-time embedded system
  • Introduced machine learning and data visualization to automate issue analysis, saving 90% of human effort

Projects

Voda Scheduler

Feb. 2021 - Nov. 2022

 https://github.com/heyfey/vodascheduler  

(30+ stars)

GPU scheduler for elastic/distributed deep learning workloads in Kubernetes cluster 

Golang, Python, Distributed Systems

  • Architected and built a GPU scheduler using microservices architecture on top of Kubernetes and various open-source projects
  • 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 heterogeneous scheduling, auto-scaling, and fault-tolerant mechanisms for the system

Publication

Tsung-Tso Hsieh, Che-Rung Lee: "Voda: A GPU Scheduling Platform for Elastic Deep Learning in Kubernetes Clusters", in IEEE International Conference on Cloud Engineering (IC2E), 2023

Education

National Tsing Hua University

Computer Science, M.S.

SCOPE Lab (Scientific Computing On Parallel Environment)

2019 - 2021

National Tsing Hua University

Double Major in Law and Computer Science, B.S.

2014 - 2018