Statistical Properties of Turbulence: An Overview

We present an introductory overview of several challenging problems in the statistical characterisation of turbulence. We provide examples from fluid turbulence in three and two dimensions, from the turbulent advection of passive scalars, turbulence in the one-dimensional Burgers equation, and fluid turbulence in the presence of polymer additives.Comment: 34 pages, 31 figure

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Path Probing Relay Routing for Achieving High End-to-End Performance 1 Division of Engineering and Applied Sciences

Abstract—We present an overlay network routing scheme, called Path Probing Relay Routing (PPRR), which is capable of promptly switching to alternative paths when the direct paths provided by the underlying IP networks suffer from serious performance degradation or outage. PPRR uses a randomized search algorithm to discover available alternative paths and employs an end-to-end, on-demand probing technique to determine their quality. To assess the effectiveness of PPRR, we conduct performance simulations using four sets of real-world traces, collected by various research groups at different times and places. Our simulation results show that the performance of PPRR is comparable to that of a typical link state relay routing algorithm. Compared with the latter, PPRR has lower probing overhead in the sense that the overhead remains constant as network size grows. In particular, PPRR avoids the need to flood the overlay network with link state updates. Keywords-overlay networks; relay routing; path probing; endto-end performance I