Linux BPF Superpowers: a talk by Brendan Gregg of Netflix at Facebook's Performance@Scale event about Linux enhanced BPF (aka eBPF) for performance analysis.
12 eBPF-Powered CLI Utilities That Every Modern Linux Sysadmin Should Master
Classic Linux tools are always there, but eBPF is the natural upgrade as it looks directly in the kernel. Once you start using these tools, it’s hard to imagine managing Linux systems without them.
eBPF and Kubernetes: Little Helper Minions for Scaling Microservices - Daniel Borkmann, Cilium
mitchellh/libxev
libxev is a cross-platform, high-performance event loop that provides abstractions for non-blocking IO, timers, events, and more and works on Linux (io_uring or epoll), macOS (kqueue), and Wasm + WASI. Available as both a Zig and C API.
clem 🤗 on Twitter / X
We just released an hf CLI extension to detect the best model/quant for a user's hardware and then spins up a local coding agent. Time to go local/private/free/fast for your agents thanks to open-source! pic.twitter.com/LcVJzGCqWx— clem 🤗 (@ClementDelangue) March 17, 2026
Compiling Models to Megakernels
Fine-grained synchronization, deep pipelines, and zero kernel launch overheads, automatically.
An inside look at gRPC - performance, testing and load balancing, Mon, Jul 22, 2024, 6:00 PM | Meetup
Agenda: 5:30 Doors open 6:00 - 6:05: Announcements 6:05 - 6:30: The rest of the iceberg: performance and testing of the gRPC libraries - Ashley Zhang and AJ Heller 6:30 - 7
Reading a Performance Profile: Field Guide
An interactive field guide to the Chrome DevTools Performance panel: waterfall, flame chart, LCP, CLS, INP, and the Insights panel.
FOSDEM 2022 - LibVF.IO: vGPU & SR-IOV on Consumer GPUs using Nim
I'd like to showcase LibVF.IO's new LIME Runtime feature (Lime Is Mediated Emulation) and do a deep dive on open source vGPU technology in general.
Jacky Kwok on Twitter / X
Scaling self-verification with DeepSeek V4 Flash beats Claude Fable 5 on Terminal-Bench 2.1, while being 11x cheaper 💰As open-source models become more capable, they can now generate large numbers of high-quality candidate solutions and verify their own outputs at very low… https://t.co/as2HtyHzzW pic.twitter.com/XzVBgr5JPz— Jacky Kwok (@jackyk02) August 17, 2026
Benchmarks | EXO
Transparent benchmarks for LLMs tested on real hardware. Coming soon.
Launching QuickDID - Fast, Open Handle Resolution for the AT Protocol - Nick's Blog
QuickDID is a high-performance, open source handle resolution service for the ATmosphere that serves as both public infrastructure at https://quickdid.smokesignal.tools and deployable software under MIT license. It offers flexible caching strategies (memory/Redis/SQLite), scales from single-instance to distributed deployments, and includes production features like rate limiting and proactive cache refresh. Currently a release candidate, it provides a drop-in alternative to Bluesky's resolver while giving developers full control over their handle resolution infrastructure.
The HDF5® Library & File Format - The HDF Group - ensuring long-term access and usability of HDF data and supporting users of HDF technologies
HDF5® Technical Details License: BSD-style Official Media Type: application/vnd.hdfgroup.hdf5 Standard File Extension: .h5, .hdf5 High-performance data management and storage suite Utilize the HDF5 high performance data software library and file format to manage, process, and store your heterogeneous data. HDF5 is built for fast I/O processing and storage. Download HDF5 Documentation What is HDF5®? HETEROGENEOUS DATA HDF® sup ports […]
#brainfoundationmodels #neuroai #eeg #meg #fmri #neuroscience #machinelearning #opensource #fair | Jarod Lévy
Today, the Brain&AI team announces a new release with NeuralBench. 📊📊📊 A unified framework for benchmarking foundation models of brain activity. This wouldn’t have been possible without the tremendous work of Hubert Banville 🎉 🎉 🎉 - 🧠 36 EEG tasks - 🗄️ 94 public datasets. - 💻 Code: https://lnkd.in/dPDMwja3 - 📄 Paper: https://lnkd.in/ddDU2p6d This package allows systematic evaluation of any foundation models. NeuralBench addresses this by defining each task end-to-end with config files (data source, preprocessing, splits, optimizer, metrics, architecture) so all models can be evaluated on the same footing. We invite the community to contribute new tasks, datasets, and models, especially for fMRI, MEG, and iEEG. The long-term goal is a fully unified benchmark across neuroimaging tasks and modalities. What's in the first release, NeuralBench-EEG v1.0: - 36 EEG tasks across 94 public datasets, spanning motor imagery, clinical classification, cognitive decoding, and phenotype prediction. - Task-specific deep learning architectures (EEGNet, Deep4, EEGConformer, CTNet, ...) benchmarked side-by-side with recent EEG foundation models (BENDR, LaBraM, BIOT, CBraMod, LUNA, REVE). - Extensible to other neuroimaging modalities: the framework already runs MEG and fMRI tasks, leveraging our NeuralSet ecosystem for accessing brain imaging data and the broader neuroscientific software stack. - Released under the MIT license. Big team effort with Stéphane d'Ascoli, Simon Dahan, Jérémy RAPIN, Marlène Careil, Yohann Benchetrit, Saarang P., Antoine Ratouchniak, Lucy (Mingfang) Zhang, Elisa Cascardi, Katie Begany Teon Brooks, and Jean-Rémi King. And special thanks: Alexandre Gramfort Thomas Moreau Arnaud Delorme Bruno A. Pierre Guetschel #BrainFoundationModels #NeuroAI #EEG #MEG #fMRI #Neuroscience #MachineLearning #OpenSource #FAIR
How to Scale a System from 0 to 10 million+ Users
Scaling is a complex topic, but after working at big tech on services handling millions of requests and scaling my own startup (AlgoMaster.io) from scratch, I’ve realized that most systems evolve through a surprisingly similar set of stages as they grow.
An unordered / non-exhaustive list of things that helped scale Bluesky's infra efficiently: + Exiting the cloud (colocation) + HAProxy w/many Node backends + Go w/clever code + ScyllaDB + SQLite w/per user databases + Redis w/many instances + AMD servers w/many cores + Purchasing bandwidth directly
