Server Intern

ZHEN WANG

**** **** ***** **, **********, Texas *5080

(682) ·241 · 5806 ****.*****@********.*** LinkedIn EDUCATION

The University of Texas at Dallas Aug. 2019 - present Ph.D. Candidate & MS in Computer Engineering, GPA: 3.7/4 China University of Geosciences Sep. 2014 - Jul. 2018 B.S. in Electrical Engineering, GPA: 88/100, Rank: 1/33 TECHNICAL SKILLS

Computer Languages C, C++, Golang, Rust, JavaScript, Python, Java, PHP, Verilog Tools and Platforms In-depth understanding of Kubernetes, OpenFaaS, Linux, Git Node.js, Express, HTML, React, CUDA, Tensorflow,

microcontroller programming, LabVIEW, IC design

WORK EXPERIENCE

VMware, Inc. May 2022 - Aug 2022

Intern - Member of Technical Staff - Distributed Edge Team Palo Alto, CA

· Work with 5+ researchers and developers in user-centric co-innovation to unravel the complexities of distributed adaptive systems anticipated with the ever-increasing amalgamation of cloud & edge.

· Investigated opensource edge native WebAssembly projects and summarize reports and research ideas.

· Implemented Rust library for math and ML functions runnable in distributed edge runtime to support adaptive policy execution.

· Customized Kubernetes webhook and integrated it with WebAssembly serverless framework. PROJECTS

Online Food Order Website

· Built a full-stack interactive food order website by combining techniques such as JavaScript and HTML.

· Constructed REST-API based backend support using Node.js server and Express framework.

· Utilized MongoDB as the backend database and implemented Redis cache service to increase read speed by 3.8, exploit EJS templeate as the frontend display engine and AJAX-based asynchronous communication. Intelligent WebAssembly-based Edge Serverless Framework

· Systematically characterized major server-side WebAssembly runtimes for edge scenario. Identified the backend compiler inefficiencies of the runtimes and simulate hardware enhancement through gem5.

· Modified serverless framework OpenWhisk and added WebAssembly-based OpenWhisk executor in place of container for meeting the stringent edge resources and latency requirement.

· Designed a XGBoost-based intelligent scheduler using code features and microarchitecture metrics to sched- ule the request to the appropriate WebAssembly executor for reducing cold start latency by 120%. Cloud-native HTTP Server

· A HTTP server written in Golang, containerized, and deployed on Kubernetes.

· Graceful termination and startup were supported; Metrics were collected by the server and sent to the Prometheus server, and finally visualized on Web UI.

· Exposed the service as Istio Ingress Gateway.

Mutual Exclusion Across Distributed Fileservers

· Built a cluster comprises five clients and three servers that store multiple consistent files. Each client can modify the files on each server without losing consistency across all servers.

· Written in C++. Multi-threads for handling network building and communication.

· Adopted Ricart-Agrawala algorithm and Lamport logical clock for mutual exclusion. PUBLICATION

[1] Z. Wang, J. Wang, Z. Wang, Y. Hu, “Characterization and Implication of Edge WebAssembly Run- times”, HPCC 2021.

[2] Z. Wang, “Survey of Serverless Computing: a System Designer’s Perspective”, under preparation.

[3] J. Wang, Z. Wang, W. Wu, Y. Hu, “ Unveiling the Micro-Architectural Performance of the Current Edge NFV Network and the Emerging 5G NFV System“, IEEE Transactions on Network Science and Engineering 2022, major revision

[3] Y. Gao, Z. Wang, et al. “EIF: a Mediated Pass-Through Framework for Inference as a Service”, DAC 2022, under review.

[4] Z. Wang, X. Zeng, X. Tang, D. Zhang, Z. Wang, et al. “Demystifying Arch-hints for Model Extraction: an Attack in Unified Memory System”, ISCA 2022, under review

[5] Z. Wang, J. Wang, Z. Wang, Y. Hu, “Implication of WebAssembly at the Edge”, DAC-WIP 2021.

[6] Z. Wang, Z. Wang, C. Liu, Y. Hu. “Understanding and Tackling the Hidden Latency for Edge-based Heterogeneous Platform”, USENIX HotEdge 2020.

[7] Z. Wang, Z. Jiang, Z. Wang, et al. “Enabling Latency-aware Data Initialization for Integrated CPU/GPU Heterogeneous Platform in Driving Automation”, EMSOFT 2020 & IEEE TCAD.

[8] Z. Wang, C. Sun, et al., “A Widely Amplitude-adjustable Chaotic Oscillator Based on a Physical Model of HP Memristor”, IEICE Electronics Express, 2018. AWARDS & HONORS

Mary and Richard Templeton Fellowship 2022, The University of Texas at Dallas CSAW Logic Locking Conquest Finalist Travel Award 2019, Cybersecurity Games & Conference (CSAW) National Endeavor Scholarship 2016, Chinese Ministry of Education

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