Phoronix paints a very different picture, especially in non-synthetic workloads[1]. Gravitron2 looks like a nice speedup over the first generation but either the optimization isn't there yet or there are areas which need additional work to become more developer/HPC competitive. That said, I'm thrilled we have competition in the architecture space for general purpose compute again.
Disclosure: I work for AWS on cloud infrastructure
My personal opinion is that the Phoronix way places quantity over quality. Measuring performance is an important part of shining a light on where we can improve the product, but I get little practical information from those numbers, even when they are reported as non-synthetic. There are HPC workloads that are showing significant cost advantages when run on C6g, like computational fluid dynamics simulations. See [1].
I expect the scalability of HPC clustering to improve on C6g in the future, like C5n improved cluster scalability compared to C5 with the introduction of the Elastic Fabric Adapter. The Phoronix and Openbenchmarking.org approach doesn't give much insight into workloads like this.
My advice for an audience like folks on HN is is to test it for yourself. For me, being able to run my own experiments is how I come to understand infrastructure better. And the cloud lowers the barrier of running those experiments significantly by being available on-demand, just an API call away. I'd love to hear what you think, either in a thread here or you can contact me via addresses in my user profile.
Didn't go too deep into it, but the AMD cpus being compared are different. Anandtech has an AWS-only EPYC 7571 (2 socket, 32 cores each, 2.5ghz), Phoronix has EPYC 7742 (1 socket, 64 cores, 2.2ghz). On top of that, Anandtech is using another AWS ec2 instance and Phoronix is testing on a local machine on bare metal.
Still would be interesting to know what differences caused the gap in results, but their setups were pretty different.
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We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software designed to handle hundreds of millions of API calls? Want to design next generation user interfaces? Want to scale the state of the art in machine learning systems? jobs at blackbird.am
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Implicit is basically just an implementation detail. The idea of only allowing one typeclass instance per data is generally referred as confluence and you're correct in that scala doesn't attempt to enforce it.
I understand the Haskell communities desire for coherent typeclasses, but I still find the newtype work around cludge to allow multiple implementation of, say, Monoid to be quasi hacky. What's worse, you can still fairly easily define multiple instances of the same typeclass accidentally (orphan instances) and the compiler won't catch it.
Menlo Park, Ca - Full time - Onsite - Frontend, AI Systems, Dev Ops
Blackbird is a ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) and a polyglot AI stack written in everything from Python to Scala to Haskell.
We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software designed to handle hundreds of millions of API calls? Want to design next generation user interfaces? Want to scale the state of the art in machine learning systems? jobs at blackbird.am
Clearly a chatroom with half a million individuals is unusable from pretty much every perspective. That said, a chat server with N chatrooms and a total population of 500k users sounds like a good day on IRC and well within the realm of what something like this could potentially handle.
That depends very much on what's doing the chatting. If it's code chatting with other code -- for example, mobile devices receiving near-real-time notifications -- then half a million is just getting started.
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Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.
We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.
The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.
We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am
Menlo Park, Ca - Full time - Onsite - Frontend, Backend, Dev Ops, ML/AI
Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.
We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.
The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.
We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am
Menlo Park, Ca - Full time - Frontend, Backend, Dev Ops, ML/AI
Blackbird is a stealth, ventured backed, artificial intelligence technology company focused on solving some important challenges created by the shift from desktop to mobile. Our stack is primarily in functional style Scala (we are heavy functional programming users) with most of our AI stack in Python and C++.
We're one of a few startups that do AI research above and beyond product development. We host regular talks on multiple disciplines ranging from systems to functional programming to deep learning.
The team was founded by former Stanford CS graduates that built self driving cars, search at Google and Yahoo Research, co-authored the google file system and scaled Twitter to 200 million users. Our open source code powers Snapchat, Tumblr, Wikipedia in production today.
We're currently looking to add some great engineers to our team. Want to write highly scalable software with the architects who scaled Twitter and Google? Want to run ops for software which is designed for fault tolerance? Want to design next generation user interfaces? jobs at blackbird.am
[1] https://www.phoronix.com/scan.php?page=article&item=epyc-vs-...