Remove 2014 Remove Benchmarking Remove Database Remove Design
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AMD EPYC Processors in Azure Virtual Machines

SQL Performance

Both of these Intel processors are special bespoke models that are not in the Intel ARK database. I wrote about using CPU-Z to benchmark the Intel Xeon E5-2673 v3 processor in an Azure VM in this article. The older Intel Xeon E5-26xx v3 (Haswell) series which was introduced in Q3 of 2014, had a maximum memory bandwidth of 2133MHz.

Azure 42
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SQL Server 2016 – It Just Runs Faster: Always On Availability Groups Turbocharged

SQL Server According to Bob

As we moved towards SQL Server 2014, the pace of hardware accelerated. While we were confident in the design of SQL Server 2012, several customers reported to us performance problems that did not appear to be with disk subsystems, CPU, or networks. Our design needed to scale and be adaptable to the modern hardware on the market.

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The Performance Inequality Gap, 2021

Alex Russell

Devices and networks have evolved too: Alex Russell @slightlylate An update on mobile CPUs and the Performance Inequality Gap: Mid-tier Android devices (~$300) now get the single-core performance of a 2014 iPhone and the multi-core perf of a 2015 iPhone. mid-priced Androids were slightly faster than 2014's iPhone 6.

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Progress Delayed Is Progress Denied

Alex Russell

As an engineer on a browser team, I'm privy to the blow-by-blow of various performance projects, benchmark fire drills, and the ways performance marketing (deeply) impacts engineering priorities. With each team, benchmarks lost are understood as bugs. Delayed three years ( Chrome 40, November 2014 vs. Safari 11.1,

Media 145
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Real-Real-World Programming with ChatGPT

O'Reilly

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.

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Data Mining Problems in Retail

Highly Scalable

Although these problems are very different, we are trying to establish a common framework that helps to design optimization and data mining tasks required for solutions. The design of the model heavily depends on the problem. This model helps to design targeted usage expansion campaigns. Propensity to category expansion.

Retail 152