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5.5 mm in 1.25 nanoseconds

Randon ASCII

In 2004 I was working for Microsoft in the Xbox group, and a new console was being created. One benchmark I wrote measured the L2 cache latency. With fixed hardware it’s easy to construct a linked list that will stay in L1, or will always require a trip to L2, or will always require a trip to main memory. So, anyway.

Cache 126
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File systems unfit as distributed storage backends: lessons from ten years of Ceph evolution

The Morning Paper

Breaking that assumption allowed Ceph to introduce a new storage backend called BlueStore with much better performance and predictability, and the ability to support the changing storage hardware landscape. But let’s take a quick look at the changing hardware landscape before we go on… The changing hardware landscape.

Storage 64
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SQL Server I/O Basics Chapter #1

SQL Server According to Bob

Microsoft SQL Server I/O Basics Author: ​​ Bob Dorr, Microsoft SQL Server Escalation Published: ​​ December, 2004 SUMMARY: ​​ Learn the I/O requirements for Microsoft SQL Server database file operations. © ​​ 2004 Microsoft Corporation. ​​ All rights reserved.

Servers 40
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SQL Server I/O Basics Chapter #2

SQL Server According to Bob

ReadFile WriteFile ReadFileScatter WriteFileGather GetOverlappedResult ​​ For extended details on the 823 error, see ​​ Error message 823 may indicate hardware problems or system problems ​​ ( [link] i crosoft.com/default.aspx?scid=kb ​​ Contact your hardware manufacture for assistance.

Servers 40
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Amazon DynamoDB ? a Fast and Scalable NoSQL Database.

All Things Distributed

Amazon DynamoDB offers low, predictable latencies at any scale. A number of outages at the height of the 2004 holiday shopping season can be traced back to scaling commercial technologies beyond their boundaries. s read latency, particularly as dataset sizes grow. Another important requirement for Dynamo was predictability.