Driving One's Own Audio Device
The device driver interface offers other device methods in addition to the open/close and read/write pairs. While none of them is critical to device operation, I usually add a few lines of code to implement select and lseek. The former is needed by those programs which multiplex several input/output channels or use non-blocking operations to read and write data. Its role is quite needed if you run real programs, and the implementation is straightforward enough that I won't show it here. The implementation of lseek, on the other hand, consists of the one line return -ESPIPE; and is meant to tell any program that tries to lseek the device that this “is a pipe” (reported to user space as “Illegal seek”).
My aversion to computer sound makes me a novice in the field, and I really don't know anything about programs that play audio, or sites where audio files can be retrieved. Although Linus Torvalds offered an interesting “I pronounce Linux as Linux”, the file was not enough to test my device, and I needed to generate some audio data. The result is the sad distribution includes a program that plays sinusoidal waves, one that plays square waves and a not-so-good piano implementation. These tools work with any /dev/audio you happen to run and can be fun to play with, especially if you have a scope near your Linux box.
All code for the sad program is available by anonymous download in the file ftp.linuxjournal.com/pub/lj/listings/issue53/2997.tgz.

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Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.
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