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Seamless offloading of web app computations from mobile device to edge clouds via HTML5 Web Worker migration

The Morning Paper

Edge servers are the middle ground – more compute power than a mobile device, but with latency of just a few ms. These use their regression models to estimate processing time (which will depend on the hardware available, current load, etc.). This could of course be a local worker on the mobile device.

Mobile 104
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A case for managed and model-less inference serving

The Morning Paper

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. First off there still is a model of course (but then there are servers hiding behind a serverless abstraction too!). autoscaling).

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The Three Types of Performance Testing

CSS Wizardry

The short answers are, of course ‘all the time’ and ‘everyone’, but this mutual disownership is a common reason why performance often gets overlooked. Of course, it is impossible to fix (or even find) every performance issue during the development phase. The reason I refer to this as Proactive testing is becasue we generally do.

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SRE Incident Management: Overview, Techniques, and Tools

Dotcom-Montior

We are kidding of course, but you know something is bad if happens that early in the morning. Software services still require physical devices and hardware for them to function. Knowing when and where an error, downtime, or application latency occurs is a critical factor in limiting the impact to users and customers.

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What is a Distributed Storage System

Scalegrid

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. They maintain fault tolerance and redundancy by replicating this information throughout various nodes in the system.

Storage 130
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Snap: a microkernel approach to host networking

The Morning Paper

Snap: a microkernel approach to host networking Marty et al., This paper describes the networking stack, Snap , that has been running in production at Google for the last three years+. The desire for CPU efficiency and lower latencies is easy to understand. Upgrades are also rolled out progressively across the cluster of course.

Network 92
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This spring: High-Performance and Low-Latency C++ (Stockholm) and ACCU (Bristol)

Sutter's Mill

Tue-Thu Apr 25-27: High-Performance and Low-Latency C++ (Stockholm). On April 25-27, I’ll be in Stockholm (Kista) giving a three-day seminar on “High-Performance and Low-Latency C++.”

Latency 51