🗓️ TOMORROW: March 19 at 11 am ET/4 pm CET ✨ P4 Developer Day || SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate with Murayyiam Parvez 🎟️ Register here:… | P4 Langua
🗓️ TOMORROW: March 19 at 11 am ET/4 pm CET ✨ P4 Developer Day || SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate with Murayyiam Parvez 🎟️ Register here: https://lnkd.in/dMZWEVBj Abstract: Machine learning is increasingly used in programmable data planes, such as switches and smartNICs, to enable real-time traffic analysis and security monitoring at line rate. Decision trees (DTs) are particularly well-suited for these tasks due to their interpretability and co
Huge congratulations, Venkat Kunaparaju! 🎉 It has been a pleasure having you as part of our NextGArch Lab since 2023 ... quickly standing out for your initiative, technical depth, and ability to… |
Huge congratulations, Venkat Kunaparaju! 🎉 It has been a pleasure having you as part of our NextGArch Lab since 2023 ... quickly standing out for your initiative, technical depth, and ability to turn ideas into real systems work. Your contributions to our GigaFlow work on scalable fast paths for Open vSwitch and SmartNICs have been outstanding—presenting it at TechCon and then taking it through HotCHIPs and ASPLOS! 🙏 For an undergraduate student to contribute at this level—across architect
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Michigan Housing Honored Instructors
Since 2018, Michigan Housing has provided residential students an opportunity to honor the instructors who make a positive impact on their collegiate journey at the University of Michigan. Michigan Housing is excited to continue to celebrate the incredible faculty and instructors that inspire our students each and every day.
For our next OCPTAP session, we have Ertza Warraich, systems and networking researcher and recent Ph.D. graduate from Purdue University. Ertza will present OptiNIC, a domain-specific RDMA transport… |
For our next OCPTAP session, we have Ertza Warraich, systems and networking researcher and recent Ph.D. graduate from Purdue University. Ertza will present OptiNIC, a domain-specific RDMA transport designed for large-scale distributed machine learning. His talk explores how relaxing traditional reliability and in-order delivery guarantees can dramatically reduce tail latency and improve throughput across multi-GPU, high-speed interconnects. The session will cover: • Why strict RDMA semantics be
SPLIDT Accepted to NSDI2026: Scalable Stateful Inference at Line Rate | Muhammad Shahbaz posted on the topic | LinkedIn
🚨 Big and humbling news! Our paper SPLIDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate has been accepted to #NSDI2026! 🎉 In-network ML has long been caught between a rock and a hard place—accuracy or scalability. SPLIDT says: why not both? SPLIDT reimagines how decision trees operate in programmable data planes by: • ✂️ Partitioning trees into subtrees with their own stateful features, • 🔁 Recirculating packets to reuse registers and match-action tables (MATs) ac
How ML can transform transport: A new paper on RDMA and ML | Muhammad Shahbaz posted on the topic | LinkedIn
Transport is the next frontier in accelerating foundation models, and getting there means "Reimagining RDMA Through the Lens of ML"! In our upcoming paper in IEEE CAL'25, we explore how a domain-specific focus can supercharge transport for ML workloads. https://lnkd.in/eF4EaciF This work is being spearheaded by my daring and relentless students, Ertza Warraich, Ali Imran, and Annus Zulfiqar, along with our amazing collaborators, Shay Vargaftik and Sonia Fahmy! ACM SIGARCH | Purdue Computer Sc
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SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate || P4 Developer Day
Machine learning is increasingly used in programmable data planes, such as switches and smartNICs, to enable real-time traffic analysis and security monitoring at line rate. Decision trees (DTs) are particularly well-suited for these tasks due to their interpretability and compatibility with the Reconfigurable Match-Action Table (RMT) architecture. However, current DT implementations require collecting all features upfront, which limits scalability and accuracy due to constrained data plane reso
p4.org
Gigaflow: Pipeline-Aware Sub-Traversal Caching for Modern SmartNICs – P4 – Language Consortium
Figure 1: (a) A traversal is a complete sequence of table lookups through the vSwitch pipeline that generates a Megaflow rule. (b) A sub-traversal is a subset of these lookups within a traversal, capturing smaller, reusable segments shared across multiple flows.
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.
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Gigaflow - Pipeline-Aware Sub-Traversal Caching for Modern SmartNICs (ASPLOS 2025)
Learn about Gigaflow: a high hit rate, SmartNIC-native cache for virtual switches (like OVS) that expands rule space coverage by two orders of magnitude and reduces cache misses by up to 90%. This work was presented as ASPLOS'25.