Tootfinder

Do you have a long running calculation freezing up your shiny app? {callr} or {crew} might help: https://discindo.org/post/asynchronous-execution-in-shiny/

@ddprrt wrote an article about async Rust in a nutshell, with all the fundamentals you need to understand Rust async 👀
Check it out: https://www.shuttle.rs/blog/2024/02/29/async-rust

Async Rust in a Nutshell
Exploring how async Rust works, async primitives and using async in Rust traits

@ddprrt wrote an article about async Rust in a nutshell, with all the fundamentals you need to understand Rust async 👀
Check it out: https://www.shuttle.rs/blog/2024/02/29/async-rust

Async Rust in a Nutshell
Exploring how async Rust works, async primitives and using async in Rust traits

This https://arxiv.org/abs/2312.15078 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nli…

On elementary cellular automata asymptotic (a)synchronism sensitivity and complexity
Among the fundamental questions in computer science is that of the impact of synchronism/asynchronism on computations, which has been addressed in various fields of the discipline: in programming, in networking, in concurrence theory, in artificial learning, etc. In this paper, we tackle this question from a standpoint which mixes discrete dynamical system theory and computational complexity, by highlighting that the chosen way of making local computations can have a drastic influence on the pe…

Last month, we had a talk from @ddprrt about Async Rust and usage of async in Rust traits!
We've teamed up again to bring you an article that summarises async Rust while still covering the important bits that you want to know.
Check it out: https://www.shuttle.rs/blog/2024/02/29/asy

Async Rust in a Nutshell
Exploring how async Rust works, async primitives and using async in Rust traits

This https://arxiv.org/abs/2306.03623 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNE_…

Spike-based computation using classical recurrent neural networks
Spiking neural networks are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes. This property allows neural networks to make asynchronous and sparse computations and therefore drastically decrease energy consumption when run on specialised hardware. However, training such networks is known to be difficult, mainly due to the non-differentiability of the spike activation, which prevents the use of classical backpropagation. This …

This https://arxiv.org/abs/2401.05857 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Secure Dynamic Event-triggered Consensus Under Asynchronous Denial of Service
This article proposes a secure implementation for consensus using a dynamic event-triggered (DET) communication scheme in high-order nonlinear multi-agent systems (MAS) under asynchronous (distributed) denial of service (DoS) attacks. By introducing a linear auxiliary trajectory of the system, the DET data transmission scheme among the neighboring agents is employed to reduce the communication for each agent. The asynchronous DoS attacks can block each communication channel among the cooperativ…

This https://arxiv.org/abs/2104.03673 has been replaced.
link: https://scholar.google.com/scholar?q=a

Practical Byzantine Reliable Broadcast on Partially Connected Networks (Extended version)
In this paper, we consider the Byzantine reliable broadcast problem on authenticated and partially connected networks. The state-of-the-art method to solve this problem consists in combining two algorithms from the literature. Handling asynchrony and faulty senders is typically done thanks to Gabriel Bracha's authenticated double-echo broadcast protocol, which assumes an asynchronous fully connected network. Danny Dolev's algorithm can then be used to provide reliable communications between pro…

All software build systems should have the possibility to generate metadata (including trace IDs) for all the artifacts they generate (whether they are final or just intermediate results).
The same way some people add tracing metadata to internal requests in microservice architectures, and for similar reasons.
- complex build systems have so many boundaries (ipc, async...) across their execution path that it is sometimes impossible to trace back from error to its cause.