University of Illinois Urbana-Champaign
Enhancing system-level efficiency using SNICs
Abstract
dc:descriptionThe rapid increase in network bandwidth continues to outpace the scaling of single-thread CPU performance, creating a significant "datacenter tax" where host CPUs are consumed by infrastructure tasks. To address this, modern servers employ a variety of specialized hardware, including on-chip accelerators and programmable Smart Network Interface Cards (SNICs). This thesis provides a multi-faceted architectural analysis of these components, focusing on performance trade-offs, next-generation interconnects, and novel offload frameworks. First, a characterization of a modern host CPU (Intel Sapphire Rapids) versus an integrated SNIC processor (NVIDIA BlueField-3) reveals the fundamental performance and energy trade-offs of executing network functions, establishing that the optimal processing location is heavily dependent on workload intensity. Second, the host interconnect is addressed by characterizing the performance of offloading kernel subsystems (\texttt{zswap} and \texttt{ksm}) over the new Compute Express Link (CXL) protocol versus traditional PCIe. The results quantify the latency advantages of CXL for fine-grained, latency-sensitive host-accelerator communication. Third, a novel framework, AccDirect, is presented. It leverages an SNIC to orchestrate PCIe Peer-to-Peer (P2P) communication with an on-chip accelerator, the Intel Dynamic Load Balancer (DLB). An end-to-end comparison demonstrates that this approach significantly reduces system power and improves application throughput compared to traditional software-based load balancers by eliminating the host CPU from the data path. Finally, a deep-dive characterization of a novel programmable engine on a state-of-the-art SNIC, the NVIDIA BlueField-3 Data Path Accelerator (DPA), reveals its architectural properties and performance bottlenecks, highlighting the profound impact of its memory subsystem on overall performance. Collectively, these studies provide critical insights for architects and practitioners seeking to build and optimize efficient, next-generation data center systems.
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois Urbana-Champaign
- Year dc:date
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Vanavasam, Srikar
- Contributors dc:contributor
-
- Kim, Nam Sung
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- Copyright 2025 Srikar Vanavasam
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/129936