When writing software that uses any kind of API or hardware functionality, sooner or later there will be questions about what a particular API call or hardware operation is supposed to do. In principle, such questions should be answered by referring to the specification (and user documentation). I am a firm believer in writing readable and clear specs and keeping software coding to follow the spec, as that ensures future compatibility. But reality is not that simple. Things are generally better today than they used to be, though. Reading up a bit on the history of my first computer (the ZX Spectrum), I found some rather interesting cases of spec vs implementation, and “discovered functionality”.Continue reading “Code to the Spec(trum) or the Implementation”
In a blog post at Wind River, I describe how the Wind River Helix Lab Cloud system can be used to communicate hardware design to software developers. The idea is that you upload a virtual platform to the cloud-based system, and then share it to the software developers. In this way, there is no need to install or build a virtual platform locally, and the sender has perfect control over access and updates. It is a realization of the hardware communication principles I presented in an earlier blog post on use cases for Lab Cloud.
But the past part is that the targets I talk about in the blog post and use in the video are available for anyone! Just register on Lab Cloud, and you can try your own threaded software and check how it scales on a simulated 8-core ARM!
The 46th Design Automation Conference (DAC) is coming up in San Francisco in the US, last week of July. For me, this will be the first time I ever go to DAC. I have been to a couple of Design Automation and Test Europe (DATE) conferences before, but DAC is supposedly even bigger as an event for the EDA and related communities. I have the honor to be on a panel this year, as well as co-authoring a paper on software validation.
When I started out doing computer science “for real” way back, the emphasis and a lot of the fun was in the basics of algorithms, optimizing code, getting complex trees and sorts and hashes right an efficient. It was very much about computing defined as processor and memory (with maybe a bit of disk or printing or user interface accessed at a very high level, and providing the data for the interesting stuff). However, as time has gone on, I have come to feel that this is almost too clean, too easy to abstract… and gone back to where I started in my first home computer, programming close to the metal.
Yes, when does hardware acceleration make sense in networking? Hardware acceleration in the common sense of “TCP offload”. This question was answered by a very nicely reasoned “no” in an article by Mike Odell in ACM Queue called “Network Front-End Processors, Yet Again“.