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.
TL;DR — Demonstrates hardware-capability-based fine-grained memory safety and compartmentalisation on constrained embedded devices, setting a new bar for secure IoT OSes.
Atmosphere: Practical Verified Kernels with Rust and Verus
Xiangdong Chen, Zhaofeng Li 0004, Jerry Zhang, Vikram Narayanan et al.
TL;DR — Shows that practical kernel verification is achievable using Rust and the Verus verifier, bridging the gap between formal methods and production OS development.
TickTock: Verified Isolation in a Production Embedded OS
Vivien Rindisbacher, Evan Johnson 0001, Nico Lehmann, Tyler Potyondy et al.
TL;DR — Delivers machine-checked proofs of isolation properties for a real embedded OS, providing strong security guarantees without sacrificing production deployability.
μFork: Supporting POSIX fork Within a Single-Address-Space OS
John Alistair Kressel, Hugo Lefeuvre, Pierre Olivier
TL;DR — Reconciles the POSIX fork abstraction with unikernel/single-address-space designs, addressing a long-standing compatibility obstacle for library OS deployments.
Scalable Address Spaces using Concurrent Interval Skiplist
Tae Woo Kim, Youngjin Kwon, Jeehoon Kang
TL;DR — Tackles the fundamental kernel scalability problem of virtual memory area management by replacing the VMA red-black tree with a concurrent interval skiplist, yielding significant mmap/munmap throughput gains.
cache_ext: Customizing the Page Cache with eBPF
Tal Zussman, Ioannis Zarkadas, Jeremy Carin, Andrew Cheng et al.
TL;DR — Extends the eBPF programmability model to the OS page cache, enabling application-specific caching policies without kernel modifications.
Aeolia: A Fast and Secure Userspace Interrupt-Based Storage Stack
Chuandong Li 0004, Ran Yi 0004, Zonghao Zhang, Jing Liu 0074 et al.
TL;DR — Redesigns the storage I/O path around userspace interrupts, achieving high throughput and low latency while preserving strong isolation properties.
Sleeping with One Eye Open: Fast, Sustainable Storage with Sandman
Yanbo Zhou, Erci Xu, Anisa Su, Jim Harris et al.
TL;DR — Introduces a storage system that aggressively power-gates flash devices while maintaining low latency, addressing sustainability concerns for large-scale storage deployments.
Oasis: Pooling PCIe Devices Over CXL to Boost Utilization
Yuhong Zhong, Daniel S. Berger, Pantea Zardoshti, Enrique Saurez et al.
TL;DR — Exploits CXL interconnects to pool PCIe devices across servers, significantly improving device utilisation and laying groundwork for memory-semantic datacenter architectures.
Scalable Far Memory: Balancing Faults and Evictions
Yueyang Pan, Yash Lala, Musa Unal, Yujie Ren et al.
TL;DR — Provides a rigorous analysis of the fault-vs-eviction trade-off in far-memory systems and proposes mechanisms that scale to production datacenter workloads.
Tiga: Accelerating Geo-Distributed Transactions with Synchronized Clocks
Jinkun Geng, Shuai Mu 0001, Anirudh Sivaraman, Balaji Prabhakar
TL;DR — Exploits hardware clock synchronisation to cut coordination overhead in geo-distributed transactions, achieving latency close to the theoretical network minimum.
Pesto: Cooking up High Performance BFT Queries
Florian Suri-Payer, Neil Giridharan, Liam Arzola, Shir Cohen et al.
TL;DR — Advances Byzantine fault-tolerant systems by separating the query path from consensus, enabling high-throughput reads without weakening safety guarantees.
Orthrus: Efficient and Timely Detection of Silent User Data Corruption in the Cloud with Resource-Adaptive Computation Validation
Chenxiao Liu, Zhenting Zhu, Quanxi Li, Yanwen Xia et al.
TL;DR — Detects silent data corruption at cloud scale using resource-adaptive redundant computation, addressing a critical and hard-to-diagnose reliability threat in hyperscale infrastructure.