Shahbaz earns NSF CAREER award
03-19-2024
Muhammad Shahbaz, Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor of Computer ScienceTransforming data centers with AI
Datacenter networks are like the central nervous system, connecting and powering the technology we rely on every day. Imagine if we could make these networks even smarter and faster. That's where per-packet artificial intelligence (AI) comes in. It has the potential to revolutionize how data centers operate, making them more secure, efficient, and powerful than ever before.
Muhammad Shahbaz, Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor, in the Department of Computer Science won a National Science Foundation (NSF) CAREER award for his proposed work titled, “A Platform for Per-Packet AI using Heterogeneous Data Planes.”
His project aims to address the increasing demands on modern cyberinfrastructure by developing a holistic platform that enables datacenter operators to implement per-packet AI decisions directly within the network at line rate.
“With per-packet AI, my aim is to bridge the gap between speed and intelligence by executing AI-driven decisions directly within the heart of the network at line rate,” said Shahbaz.
This approach represents a new paradigm that merges machine learning, networking, and architecture, fostering collaboration between researchers and architects to unlock the full potential of per-packet AI in addressing evolving cybersecurity and performance requirements.
Goals of the project
This project aims to fill the gap between speed and smart decision-making in datacenter networks. It proposes a complete system where operators can use AI to make decisions for each piece of data that travels through the network, all happening at lightning-fast speeds. The project breaks down into three main parts: creating new network designs that support AI, making frameworks to easily use AI in the network, and building different AI applications to test how well the system works.
Shahbaz added, “My goal is to open new pathways for ML researchers by joining forces with network designers to make networks faster and smarter—similar to what we have seen happen between the ML and architecture communities to accelerate modern deep-learning systems like large-language models.”
This concept represents a novel approach and transcends the mere enhancement of network speed, presenting a unique opportunity for individuals with varied expertise to collaborate harmoniously. Together, they can elevate network intelligence to unprecedented levels, paving the way for innovative advancements in technology.
Real world impact
This work stands to not only improve datacenter technology, per-packet AI also creates exciting opportunities for students interested in machine learning and computer architecture. With their diverse skills and knowledge, they can now play a vital role in shaping the future of networking. For network operators, this means new job responsibility. Instead of merely designing protocols, they can become data curators, collecting valuable network data, and policymakers.
Shahbaz’s project will work to create fast and intelligent network management in next-generation datacenters and additionally solve security issues and increase performance overall.
NSF CAREER Awards
NSF CAREER awards are the organization’s most prestigious awards given to junior faculty who embody the role of teacher-scholars through research, education and the integration of those concepts within the mission of their organizations. CAREER awards support promising and talented researchers in building a foundation for a lifetime of leadership. Receiving this award reflects this project’s merit of the NSF statutory mission and its worthiness of financial support.
Muhammad Shahbaz is a Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor in Computer Science at Purdue University. His research focuses on the design and development of domain-specific abstractions, compilers, and architectures for emerging workloads (including machine learning and self-driving networks). Shahbaz received his Ph.D. and MA in Computer Science from Princeton University and B.E. in Computer Engineering from the National University of Sciences and Technology (NUST). Before joining Purdue, Shahbaz worked as a postdoc at Stanford University and a Research Assistant at Georgia Tech and the University of Cambridge. Shahbaz has built open-source systems, including Pisces, SDX, and NetFPGA-10G, that are widely used in industry and academia. He received the Facebook, Google, and Intel Research Awards; IETF/IRTF ANRP Prize, ACM SOSR Systems Award; APNet Best Paper Award; Best of CAL Paper Award; Internet2 Innovation Award; and Outstanding Graduate Teaching Assistant Award.
About the Department of Computer Science at Purdue University
Founded in 1962, the Department of Computer Science was created to be an innovative base of knowledge in the emerging field of computing as the first degree-awarding program in the United States. The department continues to advance the computer science industry through research. US News & Reports ranks Purdue CS #20 and #18 overall in graduate and undergraduate programs respectively, 6th in cybersecurity, 8th in software engineering, 13th in programming languages and systems, 15th in data analytics, and 18th in theory. Graduates of the program are able to solve complex and challenging problems in many fields. Our consistent success in an ever-changing landscape is reflected in the record undergraduate enrollment, increased faculty hiring, innovative research projects, and the creation of new academic programs. The increasing centrality of computer science in academic disciplines and society, and new research activities - centered around data science, artificial intelligence, programming languages, theoretical computer science, machine learning, and cybersecurity - are the future focus of the department. cs.purdue.edu
Writer: Emily Kinsell, emily@purdue.edu
Source: Muhammad Shahbaz, mshahbaz@purdue.edu