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"Enso: A Streaming Interface for NIC-Application Communication" https://www.microsoft.com/en-us/research/uploads/prod/2023/0...

We've been using the same API to communicate with our NICs since 1994. That API severely limits network throughput and latency. By simply changing the API (no new NIC) you can get 6x higher throughput in some apps and 43% lower latency.

Code runs on FPGA NIC only for now: https://github.com/crossroadsfpga/enso

Won USENIX OSDI best paper award and best artifact award.

This is also a good (applied, with simple code) example of the use of probabilistic programming. I can't get myself to read full books, but somehow this simple example gave me some intuition and additional pointers to follow.

For everyone else who may be similarly confused as I, due to associating this with Golang or the direction of a startup: take this title literally.

Subtitle is "Neuroscientists discover a mechanism for brain-wide communication when selecting a route toward a destination."

I really support this and am an avid cyclist myself. But this really only works in temperate (and dry) climates. If it rains, we'll have a hard time to convince people to use something without a build-in roof.

It turns out that most caching algorithms we use in practice (CDNs, memcached, storage, etc.) are still pretty far from the optimal hit ratio/ miss ratio.

See, e.g., recent work that exposes that gap (I'm an author)

https://www.cs.cmu.edu/~dberger1/pdf/2018PracticalBound_SIGM...

https://github.com/dasebe/optimalwebcaching

Yes, that paper LHD (from a colleague of mine) does use online stochastic modeling of the workload to make better decisions. So this definitely fits the bill

No, we do not expect any licensing problems. There's an open issue on github: https://github.com/dasebe/robinhoodcache/issues/1

The issue mentions 3 Clause BSD, which will probably be implemented today.

Author here: thank you pointing out the connection to parallel DBMs - I was not aware of the problem similarity but difference in approach.

Can you point me to a DBMs that does that, both an OSS or in production?

Author here: this is very much a research project with the purpose of prototyping the idea that caching can help tail latency. Previously, people didn't believe that caches can be used that way and it turns out you really have to rethink how you use the caches.

We build a testbed and replayed production workloads. This is not running in production yet. We're actively looking for new workloads and scenarios to test this at scale!

Direct link to paper: https://www.usenix.org/system/files/osdi18-berger.pdf

Repo: https://github.com/dasebe/robinhoodcache

Haven't tested this, and it's a true concern. But I would hope there's some truth to emission reductions as having a comprehensive pass (includes bikes, buses, and Helsinkis good subway system) should entice people to use these options as well. One incentive to use these other options is not needing to search for a parking spot. To make a real difference, people need to be willing to not rely on car sharing 100%, though. So maybe more incentives would be needed for this to reduce emissions in other cities.

In other countries suburban villages have been growing for centuries before cars became available (at least in parts of Europe). So, one can live in these villages without a car and can expect some level of public transportation.

I'm teaching an intro distributed systems class and would like to share this with my students. I was wondering about how general the linked interview prepwork is. Are the Anki cards and sample interview questions mostly from large companies (FB, Google, MS) or also applicable to interviewing at smaller places?

At first look, seems like these are fairly general questions, which is great.

I'm at a large research school teaching computer science. Anecdotally, I have not received pressure from administrators. I have gotten pointers about the expected number of As and Bs from senior faculty though. And, the curves do go both ways.

I'm using the Autolab project from CMU, and I'm quite satisfied. You'll need a couple machines to self host, and run the student's code.

http://www.autolabproject.com

Features:

Autograding Grade any assignment in any language using any software package. Instantly.

Scoreboards Encourage healthy competition with a real-time rank ordered scoreboard.

Code Annotation Augment the autograde with additional feedback directly on the student's code.

Cheat Detection Maintain academic integrity by comparing assessments with each other and with past submissions. Uses Stanford's Moss Cheat Detector.

Is there a chance you can point us to a code snippet of said cache algorithm, or elaborate a bit?

If it's simple and elegant in hindsight this insight might be interesting in other CS applications. Not cross sharing and reinventing wheels is a somewhat sad implication from the compartmentalization you mention.

I've tested JuNest extensively (with the idea of getting new gcc compiler features on a cluster running an old red hat version).

Unfortunately, JuNest adds a lot more overhead than containers. Specifically, when it comes to high-throughput network applications. At 10GBit an application running on JuNest used several cores at 100%, while without JuNest (underlying red hat) the app was at 10% cpu load (network i/o bound).

All that load was due to PRoot.