Annus Zulfiqar
I’m a PhD candidate in the Computer Science and Engineering department at the University of Michigan, Ann Arbor, advised by professor Muhammad Shahbaz. My research is about rethinking data plane architectures and algorithms to build scalable networked systems that overcome traditional resource limitations and adapt quickly to dynamic network conditions.
Publications
NSDI 2026
SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate
Murayyiam Parvez*, Annus Zulfiqar*, Roman Beltiukov, Shir Landau-Feibish, Walter Willinger, Arpit Gupta, Muhammad Shahbaz (*co-primary author)
ARXIV 2025
OptiNIC: A Resilient and Tail-Optimal RDMA NIC for Distributed ML Workloads
Ertza Warraich, Ali Imran, Annus Zulfiqar, Shay Vargaftik, Sonia Fahmy, Muhammad Shahbaz
Links: Paper
IEEE CAL 2025
Reimagining RDMA Through the Lens of ML
Ertza Warraich, Ali Imran, Annus Zulfiqar, Shay Vargaftik, Sonia Fahmy, and Muhammad Shahbaz
🎖️Broadcom Research Award
Links: Paper
MICRO 2025
NetSparse: In-Network Acceleration of Distributed Sparse Kernels
Gerasimos Gerogiannis, Dimitrios Merkouriadis, Charles Block, Annus Zulfiqar, Filippos Tofalos, Muhammad Shahbaz, Josep Torrellas
Links: Paper
SIGCOMM 2025 Poster
Kairo: Incremental View Maintenance for Scalable Virtual Switch Caching
Annus Zulfiqar, Ben Pfaff, Gianni Antichi, Muhammad Shahbaz
ASPLOS 2025
Gigaflow: Pipeline-Aware Sub-Traversal Caching for Modern SmartNICs
Annus Zulfiqar, Ali Imran, Venkat Kunaparaju, Ben Pfaff, Gianni Antichi, Muhammad Shahbaz
In the Media (toggle)

Tech Xplore

Gigaflow cache streamlines cloud traffic, with 51% higher hit rate and 90% lower misses for programmable SmartNICs

A new way to temporarily store memory, Gigaflow, helps direct heavy traffic in cloud data centers caused by AI and machine learning workloads, according to a study led by University of Michigan researchers.

danglingpointers.substack.com

Gigaflow: Pipeline-Aware Sub-Traversal Caching for Modern SmartNICs

Separable memoization

Knowridge Science Report

Scientists boost cloud speed with new “gigaflow” memory system

As AI and machine learning tasks put more strain on cloud computing systems, a new technology called Gigaflow could help ease the pressure. Developed by researchers at the University of Michigan and their partners, Gigaflow is a smart way of managing memory in large data centers, and it significantly improves how data is processed and […]

Computer Science and Engineering

Streamlining cloud traffic with a Gigaflow Cache

Gigaflow improves virtual switches for programmable SmartNICs, delivering a 51% higher hit rate and 90% lower misses.

SIGCOMM CCR 2023
The Slow Path Needs An Accelerator Too!
Annus Zulfiqar, Ben Pfaff, William Tu, Gianni Antichi, Muhammad Shahbaz
Links: Paper
ASPLOS 2023
Homunculus: Auto-Generating Efficient Data-Plane ML Pipelines for Datacenter Networks
Tushar Swamy, Annus Zulfiqar, Luigi Nardi, Muhammad Shahbaz, Kunle Olukotun
🎖️Distinguished Artifact Award
Links: Paper Code
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