Remove 2016 Remove Cache Remove Hardware
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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 2016 – It Just Runs Faster Announcement

SQL Server According to Bob

SQL Server 2016 ‘It Just Runs Faster’ A bold statement that any SQL Server professional can stand behind with confidence. Try SQL Server 2016 Today. In the Sep 2014 the SQL Server CSS and Development teams performed a deep dive focused on scalability and performance when running on current and new hardware configurations.

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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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Invited Talk at SuperComputing 2016!

John McCalpin

“Memory Bandwidth and System Balance in HPC Systems” If you are planning to attend the SuperComputing 2016 conference in Salt Lake City next month, be sure to reserve a spot on your calendar for my talk on Wednesday afternoon (4:15pm-5:00pm).

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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. An extension to Service Workers that enables browsers to present users with cached content when offline. is access to hardware devices. Some commenters appear to confuse unlike hardware for differences in software.

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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. 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. The second and third run used the cached data.

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