Distributed-Systems

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 ...

12 papers selected. Enhancing OmpSs-2 Suspendable Tasks by Combining Operating System and User-Level Threads with C++ Coroutines Arnau Cinca, Aleix Roca, Kevin Sala, Raúl Peñacoba Veigas et al. TL;DR — Extends the OmpSs-2 task-based runtime with C++ coroutines to implement suspendable tasks that can yield while blocked on I/O or communication without stalling the OS thread. Why notable — Suspendable tasks are a key missing primitive for overlapping computation and communication in task-graph runtimes; the hybrid OS/user-level thread design avoids the overhead of full context switches while remaining portable, with broad implications for OpenMP-style programming on modern heterogeneous nodes. ...

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. Chasing Lightspeed Consensus: Fast Wide-Area Byzantine Replication with Mercury Christian Berger 0006, Lívio Rodrigues, Hans P. Reiser, Vinicius Vielmo Cogo et al. TL;DR — Mercury is a wide-area Byzantine fault-tolerant replication protocol that minimises latency by exploiting geographic locality and pipelining to approach the theoretical lightspeed bound. Why notable — Achieving near-lightspeed latency in Byzantine replication across wide-area networks has been a long-standing open challenge; Mercury’s design demonstrates it is practically attainable. The result raises the bar for what production BFT middleware can deliver in geo-distributed deployments. ...

13 papers selected. Verus: A Practical Foundation for Systems Verification Andrea Lattuada 0001, Travis Hance, Jay Bosamiya, Matthias Brun 0002 et al. TL;DR — Verus is a Rust-based verification framework that makes formal proofs of low-level systems code tractable at scale, covering memory safety, functional correctness, and concurrency. Why notable — Formal verification of real systems code has long been impractical; Verus closes the usability gap by integrating SMT-based proofs directly into a systems programming language, making it the most broadly applicable verification tool for the OS community to date. ...

12 papers selected. Queue Management for SLO-Oriented Large Language Model Serving Archit Patke, Dhemath Reddy, Saurabh Jha, Haoran Qiu et al. TL;DR — A queue management framework that enforces latency SLOs for LLM serving by dynamically routing and prioritizing requests across heterogeneous inference capacity. Why notable — As LLM deployments move into production clouds, meeting strict time-to-first-token and total latency SLOs becomes critical; this work directly addresses that gap with a practical, deployable solution. It is one of the first papers to treat LLM serving as a cloud SLO-management problem rather than a pure model-optimization problem. ...

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.). ...

10 papers selected. Fair, Efficient Multi-Resource Scheduling for Stateless Serverless Functions with Anubis Amit Samanta 0001, Ryan Stutsman TL;DR — Anubis introduces a fair, multi-resource scheduler for stateless serverless functions that achieves efficiency without sacrificing isolation between tenants. Why notable — Fairness in serverless resource allocation is an open problem as functions compete for heterogeneous resources (CPU, memory, I/O); Anubis provides a concrete, deployable answer. The work directly addresses a gap in production FaaS platforms where existing schedulers optimize for throughput but ignore per-tenant equity. ...