Networking

10 papers selected. Parameterized Algorithms for Non-uniform All-to-all Ke Fan, Jens Domke, Seydou Ba, Sidharth Kumar TL;DR — Introduces parameterized algorithms that adapt non-uniform all-to-all collective communication to heterogeneous network topologies, reducing message contention and improving throughput. Why notable — Non-uniform all-to-all is a performance bottleneck in many HPC applications; topology-aware parameterization directly benefits MPI implementations on dragonfly and fat-tree networks at scale. → Read paper DPU-KV: On the Benefits of DPU Offloading for In-Memory Key-Value Stores at the Edge Arjun Kashyap, Yuke Li 0003, Xiaoyi Lu 0001 ...

13 papers selected. ASTERINAS: A Linux ABI-Compatible, Rust-Based Framekernel OS with a Small and Sound TCB Yuke Peng, Hongliang Tian, Junyang Zhang, Ruihan Li et al. TL;DR — A production-grade OS kernel written in Rust that exposes a full Linux ABI while confining unsafe code to a small, formally-audited framekernel core. Why notable — ASTERINAS demonstrates that Linux compatibility and memory-safety guarantees are not mutually exclusive — unsafe Rust is isolated to under 5 kloc of framework code, giving systems operators a credible path toward a safer Linux-compatible kernel without sacrificing application portability. ...

12 papers selected. Hopter: a Safe, Robust, and Responsive Embedded Operating System Zhiyao Ma, Guojun Chen, Zhuo Chen 0011, Lin Zhong 0001 TL;DR — Hopter is a new embedded OS that enforces memory safety and real-time responsiveness through a Rust-based task model with cooperative and preemptive scheduling co-designed from the ground up. Why notable — Building a ground-up safe embedded OS is a long-standing challenge; Hopter addresses it without sacrificing the determinism that IoT and robotics workloads demand, offering a credible alternative to unsafe C-based RTOSes. ...

13 papers selected. PRED: Performance-oriented Random Early Detection for Consistently Stable Performance in Datacenters Xinle Du, Tong Li 0014, Guangmeng Zhou, Zhuotao Liu et al. TL;DR — PRED redesigns AQM by making drop probability a direct function of per-flow performance targets rather than queue length, eliminating the instability of classic RED in modern datacenter workloads. Why notable — RED has been a cornerstone of congestion control for decades; PRED’s performance-centric reformulation challenges a long-held design axiom and demonstrates significantly lower tail latency at scale. It opens the door to intent-driven AQM as a first-class primitive in datacenter switches. ...

13 papers selected. Empowering WebAssembly with Thin Kernel Interfaces Arjun Ramesh, Tianshu Huang, Ben L. Titzer, Anthony Rowe 0001 TL;DR — A new OS interface design exposes thin, capability-based kernel primitives directly to WebAssembly modules, eliminating the POSIX translation layer. Why notable — WebAssembly is increasingly used beyond the browser as a portable, sandboxed compute substrate; this work shows that rethinking the system interface from scratch yields significantly lower overhead and better safety properties than layering Wasm on top of POSIX. ...

11 papers selected. DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu et al. TL;DR — Separates the compute-heavy prefill phase from the memory-bound decoding phase onto different GPU pools, eliminating head-of-line blocking and significantly improving LLM serving throughput. Why notable — Became one of the most influential LLM systems papers of 2024; the prefill–decode disaggregation insight is now widely adopted in production inference stacks (vLLM, SGLang, etc.). ...