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Bringing Rich Experiences to Memory-constrained TV Devices

The Netflix TechBlog

In a previous post , we described how our TV application consists of a C++ SDK installed natively on the device, an updatable JavaScript user interface (UI) layer, and a custom rendering layer known as Gibbon. Our UI runs on top of a custom rendering engine which uses what we call a “surface cache” to optimize our use of graphics memory.

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ZFS Is Mysteriously Eating My CPU

Brendan Gregg

I summarized this case study at [Kernel Recipes] in 2017 and have shared the full story here. ## 1. The other colors are yellow for C++, and red for other user-level code.) The ZFS Adapative Replacement Cache (ARC) is the main memory cache for the file system. A microservice team asked me for help with a mysterious issue.

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

Sutter's Mill

I don’t get to Europe very often apart from ISO C++ standards meetings, but this spring I’ve been able to accept invitations for two English-language European events in the last week of April. Tue-Thu Apr 25-27: High-Performance and Low-Latency C++ (Stockholm). Description. Sat Apr 29: ACCU closing keynote (Bristol).

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SQL Server on IoT Edge and Developer Machines – Smaller Footprint

SQL Server According to Bob

The reduction effort started when we shipped SQL Server 2017 ( [link].) The lock manager has partitions, lock block cache and other structures. Reduce the number of partitions and size of the cache. IO Request Caches. SQLPAL may cache I/O request structures with each thread. SQL Server 2017. Lock Manager.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. Here is a summary of the queries: Simple queries: select count(*) from ontime where flightdate > '2017-01-01'. The second and third run used the cached data.

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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

Bill Kaiser of NewRelic published this blog in 2017 which goes some way towards what I’m talking about, but since then I have figured out a new way to interpret the data. > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, What Is the Expected Distribution of Website Response Times? . >

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ZFS Is Mysteriously Eating My CPU

Brendan Gregg

I summarized this case study at Kernel Recipes in 2017; it is an old story that's worth resharing here. The other colors are yellow for C++, and red for other user-level code.) The ZFS Adapative Replacement Cache (ARC) is the main memory cache for the file system. I worked on this code back at Sun.

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