Remove 2016 Remove Cache Remove Hardware Remove Storage
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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

Make sure your system can handle next-generation DRAM,” [link] Nov 2011 - [Hruska 12] Joel Hruska, “The future of CPU scaling: Exploring options on the cutting edge,” [link] Feb 2012 - [Gregg 13] Brendan Gregg, “Blazing Performance with Flame Graphs,” [link] 2013 - [Shimpi 13] Anand Lal Shimpi, “Seagate to Ship 5TB HDD in 2014 using Shingled Magnetic (..)

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SQL 2016 – It Just Runs Faster: DBCC Scales 7x Better

SQL Server According to Bob

SQL Server 2016 changes the internal design to (CheckScanner), applying no lock semantics and a design similar to those used with In-Memory Optimized (Hekaton) objects, allowing DBCC operations to scale far better than previous releases. On the same hardware/machine repeat steps 1 thru 3 using an instance of SQL Server 2016 CTP 3.0

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

Make sure your system can handle next-generation DRAM,” [link] , Nov 2011 [Hruska 12] Joel Hruska, “The future of CPU scaling: Exploring options on the cutting edge,” [link] , Feb 2012 [Gregg 13] Brendan Gregg, “Blazing Performance with Flame Graphs,” [link] , 2013 [Shimpi 13] Anand Lal Shimpi, “Seagate to Ship 5TB HDD in 2014 using Shingled Magnetic (..)

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The Performance Inequality Gap, 2021

Alex Russell

Back in 2016, I gave a talk outlining the causes and effects of the terrible performance of web apps built using popular tools on the fastest-growing device segment: low-end to mid-range Android phones. A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage.

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SQL Server On Linux: Forced Unit Access (Fua) Internals

SQL Server According to Bob

Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system. Neal, Matt, and others from Windows Storage, Windows Azure Storage, Windows Hyper-V, … validating Windows behaviors. · Any storage device that can survive a power outage. Starting with the Linux 4.18

Servers 90
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Using Parallel Query with Amazon Aurora for MySQL

Percona

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. now has a version which will support parallelism for SELECT queries (utilizing the read capacity of storage nodes underneath the Aurora cluster). The second and third run used the cached data.

Cache 48
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Progress Delayed Is Progress Denied

Alex Russell

At the time of the last Confluence run, the gap had stretched to nearly 1000 APIs, doubling since 2016. Chrome has missed several APIs for 3+ years: Storage Access API. An extension to Service Workers that enables browsers to present users with cached content when offline. is access to hardware devices. Content Indexing.

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