Digests

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. ...

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. ...

12 papers selected. Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing Franck Cappello, Mario C. Acosta, Emmanuel Agullo, Hartwig Anzt et al. TL;DR — A joint JLESC survey covering error-bounded lossy compressors (SZ, ZFP, MGARD) across simulation, AI, and in-situ analytics use cases, with benchmarks on real scientific datasets at extreme scale. Why notable — The most comprehensive cross-site evaluation of scientific data compression to date, providing actionable guidance on compressor selection for different numerical kernels and accuracy requirements. ...

10 papers selected. Rethinking Computing Systems in the Era of Climate Crisis: A Call for a Sustainable Computing Continuum Ella Peltonen, Suzan Bayhan, David Bermbach, Sebastian Buschjäger et al. TL;DR — A multi-author position paper calling for carbon-aware design principles across the cloud-to-edge computing continuum, surveying energy measurement, workload scheduling, and hardware lifecycle challenges. Why notable — Establishes a community research agenda for sustainable computing infrastructure at a time when datacenter and edge energy consumption is under increasing regulatory and societal scrutiny. ...

12 papers selected. Throughput of Byzantine Broadcast Ruomu Hou, Haifeng Yu, Prateek Saxena TL;DR — Establishes tight throughput bounds for Byzantine broadcast protocols and constructs algorithms that saturate those bounds, separating throughput from latency in the fault-tolerant broadcast landscape. Why notable — Provides the first rigorous throughput characterization of Byzantine broadcast, a fundamental primitive whose capacity limits were previously unquantified. How to reduce the number of steps for (multi-valued validated) Byzantine agreement? Baohan Huang, Haibin Zhang, Chao Liu 0039, Shengli Liu 0001 et al. ...

12 papers selected. Recipe: Hardware-Accelerated Replication Protocols: Rethinking Crash Fault Tolerance Protocols for Untrusted Cloud Environments Dimitra Giantsidi, Emmanouil Giortamis, Julian Pritzi, Maurice Bailleu et al. TL;DR — Redesigns crash fault-tolerance protocols using hardware acceleration (TEEs/SmartNICs) to deliver replication with strong guarantees in untrusted cloud environments. Efficient Performance Guarantees for Function-as-a-Service with Cloud Allocators Hai Duc Nguyen 0005, Andrew A. Chien TL;DR — Introduces cloud-allocator abstractions that provide formal performance guarantees for serverless functions, addressing the unpredictability of shared FaaS infrastructure. ...

13 papers selected. Basilisk: Using Provenance Invariants to Automate Proofs of Undecidable Protocols Tony Nuda Zhang, Keshav Singh, Tej Chajed, Manos Kapritsos et al. TL;DR — Automates the construction of correctness proofs for distributed protocols that were previously considered undecidable, advancing the state of the art in verified systems. Mako: Speculative Distributed Transactions with Geo-Replication Weihai Shen, Yang Cui, Siddhartha Sen 0001, Sebastian Angel et al. TL;DR — Combines speculative execution with geo-replication to deliver low-latency distributed transactions without sacrificing consistency, addressing a fundamental tension in wide-area systems. ...

15 papers selected. Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability Nicholas Frontiere, J. D. Emberson, Michael Buehlmann, Esteban M. Rangel et al. TL;DR — Delivers the first trillion-particle cosmological hydrodynamics simulation on exascale hardware, demonstrating sustained petaflop-scale performance on a flagship scientific application. Ab-initio Quantum Transport with the GW Approximation, 42, 240 Atoms, and Sustained Exascale Performance Nicolas Vetsch, Alexander Maeder, Vincent Maillou, Anders Winka et al. TL;DR — Achieves sustained exascale performance for first-principles quantum transport at 42,240 atoms, establishing a new scale record for the GW many-body perturbation method. ...

12 papers selected. lm-Meter: Unveiling Runtime Inference Latency for On-Device Language Models Haoxin Wang 0003 TL;DR — Provides the first detailed runtime profiling framework for on-device LLM inference, revealing key latency bottlenecks across diverse edge hardware configurations. SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving Xiangchen Li TL;DR — Adapts speculative decoding to edge serving constraints, reducing LLM token generation latency while respecting the tight memory and compute budgets of edge nodes. ...

13 papers selected. From Bottleneck to Breakthrough: Optimizing Scheduling for Hyperscale Containerized Clusters Bing Li, Yuquan Ren, Xinyi Song, Zhilei Liu et al. TL;DR — Documents production-scale scheduling improvements at a hyperscale cloud provider, demonstrating how targeted optimizations reduce scheduling tail latency and increase cluster utilization in real containerized workloads. CPU-Limits kill Performance: Time to rethink Resource Control Chirag C. Shetty, Sarthak Chakraborty, Hubertus Franke, Larisa Shwartz et al. TL;DR — Challenges the conventional use of CPU cgroup limits in cloud environments, showing through production evidence that CFS bandwidth throttling degrades application QoS and proposing a rethink of resource control abstractions. ...

14 papers selected. LithOS: An Operating System for Efficient Machine Learning on GPUs Patrick H. Coppock, Brian Zhang, Eliot H. Solomon, Vasilis Kypriotis et al. TL;DR — Designs a dedicated OS for GPU ML workloads, rethinking scheduling and resource management at the kernel level for accelerator-centric computing. CHERIoT RTOS: An OS for Fine-Grained Memory-Safe Compartments on Low-Cost Embedded Devices Saar Amar, Tony Chen, David Chisnall, Nathaniel Wesley Filardo et al. ...

12 papers selected. RV-CURE: A RISC-V Capability Architecture for Full Memory Safety Yonghae Kim, Anurag Kar, Jaewon Lee, Jaekyu Lee et al. TL;DR — Extends the RISC-V ISA with hardware capabilities to enforce full memory safety—including bounds checking and pointer provenance—across the entire software stack. Why notable — Demonstrates that capability-based memory safety can be integrated into an open ISA at low cost, with implications for deploying safe-by-default embedded and server systems. ...

12 papers selected. DRKC: Deep Reinforcement Learning Enhanced Microservice Scheduling on Kubernetes Clusters in Cloud-Edge Environment Jian Jiang, Qianmu Li, Pengchuan Wang, Yunhuai Liu TL;DR — DRKC uses deep reinforcement learning to schedule microservices across Kubernetes clusters spanning cloud and edge nodes, optimizing latency and resource utilization. Why notable — One of the few papers to tackle DRL-based microservice placement at the Kubernetes level in a real cloud-edge topology, making it directly actionable for practitioners. ...

10 papers selected. Whole-system Persistence Made Efficient with Tree-structured Checkpointing on Microkernel Mingkai Dong, Fangnuo Wu, Gequan Mo, Haibo Chen TL;DR — A microkernel-based whole-system persistence scheme uses tree-structured incremental checkpointing to achieve low-overhead, crash-consistent snapshots of the entire OS state. Why notable — Whole-system persistence is a foundational building block for reliable systems; this paper shows it can be done efficiently within a microkernel architecture. XpuTEE: A High-Performance and Practical Heterogeneous Trusted Execution Environment for GPUs Shulin Fan, Zhichao Hua, Yubin Xia, Haibo Chen ...

12 papers selected. HARMONIC: Uncertainty-Aware Multi-Objective Optimization for Energy-Efficient HPC Resource Management Kyrian Adimora, Hongyang Sun 0001 TL;DR — HARMONIC applies uncertainty-aware multi-objective optimization to jointly minimize energy consumption and maximize performance for HPC resource allocation. Why notable — It directly addresses the growing demand for energy-proportional HPC scheduling with principled probabilistic models, making it relevant to both system designers and green-computing researchers. MIST: Towards MPI Instant Startup and Termination on Tianhe HPC Systems Yiqin Dai, Ruibo Wang, Yong Dong, Min Xie et al. ...

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. ...