distributed-computing

Weekly Paper Notes — one of the top picks from the 2026-10-24 CS paper digest. Area: Distributed Computing. Authors: Clément Burgelin, Rachid Guerraoui, Zicong Hong, Yinan Hu, Anne-Marie Kermarrec, Rafael Pires, Rasmus Moorits Veski, Martijn de Vos (EPFL; alphabetical order) arXiv: 2610.30114 · PDF TL;DR The title asks a question and the last section answers it: “Our answer is no; this is just a new beginning.” The EPFL distributed computing group asks whether a coding agent can produce a practical new consensus protocol: designed, implemented, benchmarked under geo-replication, crash-tested and proved safe....

Weekly Paper Notes — one of the top picks from the 2026-10-03 CS paper digest. Area: Distributed Computing. Authors: Stuart H. Sul, Nash Brown (Stanford, Cursor Research), Henry Wildermuth, William Lin, Federico Cassano (Cursor Research), Christopher Ré (Stanford) arXiv: 2609.36070 · PDF · Code TL;DR Mixture-of-Kittens (MoK) is the MoE training kernel Cursor uses to train Composer on GB300 NVL72 racks. The paper’s opening finding is uncomfortable for anyone who has invested in MoE communication libraries: on a 72-GPU NVLink domain, existing expert-parallel systems built for InfiniBand often lose to a naive PyTorch + NCCL baseline, and in nearly half of the evaluated configurations the naive baseline beats every alternative....

Weekly Paper Notes — one of the top picks from the 2026-08-08 CS paper digest. Area: Distributed Computing / Computer Architecture. Authors: Jirong Yang, Peizhe Liu, Jovan Stojkovic (UT Austin); Chaojie Zhang (Microsoft Azure) arXiv: 2608.04458 · PDF TL;DR Datacenter servers have been optimized for two workload shapes: CPU-centric services (web serving, key-value stores, analytics) and monolithic LLM inference, where a GPU does dense tensor math and the host merely feeds it....

Weekly Paper Notes — one of the top picks from the 2026-07-11 CS paper digest. Area: Distributed Computing / Systems. Authors: Hannah Atmer, Thiemo Voigt, Yuan Yao, Stefanos Kaxiras (Uppsala University) arXiv: 2607.08407 · PDF TL;DR DRAM is the choke point of the current generative-AI buildout. HBM3e stacks are backordered, contract prices are up, and hyperscalers are absorbing a large fraction of global DRAM output just to fan the same model weights out to ever more accelerators....

Weekly Paper Notes — Seminal Paper of the Week for the 2026-06-27 CS paper digest. Area: Distributed Computing. Author: Satoshi Nakamoto Published: October 31, 2008 (cryptography mailing list) Canonical URL: bitcoin.org/bitcoin.pdf This week’s digest had a fresh paper on transaction-fair ordering on DAGs without weak edges (Tilikum, 2606.27250) — a piece of work whose entire problem statement (DeFi, BEV, reordering attacks) only exists because of one nine-page document published seventeen-and-a-half years ago to a small cryptography mailing list....

Weekly Paper Notes — one of the top picks from the 2026-06-20 CS paper digest. Area: Distributed Computing. Authors: Jiasheng Zhou, Longbin Zeng, Clavis Chen, Ruiming Lu et al. arXiv: 2606.20374 · PDF TL;DR ARGUS is a tracing and performance-diagnosis system designed for always-on operation on production LLM training clusters with more than 10,000 GPUs. The central insight is that no single profiler can be cheap, deep, and continuous all at once — so ARGUS decomposes observation along the training call hierarchy into three independent collection channels: CPU call stacks, framework semantics, and GPU kernel execution....

Weekly Paper Notes — one of the top picks from the 2026-06-13 CS paper digest. Area: Distributed Computing. Authors: Samuel Erickson, Mikael Johansson (KTH) arXiv: 2606.13287 · PDF TL;DR In asynchronous SGD (ASGD), workers compute gradients on possibly stale parameters and push updates without waiting for slow peers. That’s how you keep all the GPUs busy, but it’s also how slow workers (“stragglers”) inject large delays into the update stream, which classical analyses say should slow convergence in proportion to the maximum delay across the workers....