Lock Convoys, AI Hardware, Lambda Observability, and AI for Science
- The Convoy Phenomenon (Adrian Colyer) — locks on resources that lead to performance degradation which never recovers, a situation first described in 1979.
- AI is Changing the Entire Nature of Compute (ZD) — workloads have been doubling every 3.5 months, while our post-Moore’s law chip speed increases have been 3.5% per year. What that means, both authors believe, is that the design of chips, their architecture, as it’s known, has to change drastically in order to get more performance out of transistors that are not of themselves producing performance benefits. The article explores some of those directions.
- The Annoying State of Lambda Observability — In the current state of the world, the available strategies boil down to either: (1) Send telemetry directly to external observability tools during Lambda execution. (2) Scrape or trigger off the telemetry sent to CloudWatch and X-Ray to populate external providers. Spoiler: neither option is ideal.
- Accelerating Science: A Computing Research Agenda — I found this quite challenging at first because it seemed to be “cheating” somehow. But once I viewed it as the computer augmenting the human, not replacing them, then it was more acceptable. But I can imagine that better tools for each step of the scientific journey (e.g., Expressing, reasoning with, updating scientific arguments (along with supporting assumptions, facts, observations), including languages and inference techniques for managing multiple, often conflicting arguments, assessing the plausibility of arguments, their uncertainty and provenance) will create controversy no less than the software “proof” of the four-color theorem did.
Continue reading Four short links: 2 July 2019.