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20 Nov 2020 18:07:53 UTC
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1 of 9 - Introduction
Hi, I'm Al Johnston, a network engineer who in retirement has turned to music to fill up my leisure time. I never cared much for computer gaming or for end-user applications while I was out there building and salvaging networks for corporations, but about 2001 I came across my "killer app," music notation software. I had always dreamed of writing symphonic music since I was a kid. The potential to write music as easily as one could write words on a computer intrigued me and I began to work with music software of all descriptions. Along the way I have had many discoveries and also many disappointments, but I never quit. I trusted that I was not alone in my dream to write music. Surely some day, popular demand to easily write music and hear it with listenable results would drive some company to market a product that would satisfy me.
The resulting experience I gained I will relate in four music networking tutorials which I post here on my LBRY channel: 1) "How I built my own server-class music workstation," 2) "How to network music workstations together," and 3) "Sibelius as scoring editor," and 4) "Sibelius as scoring editor - Part 2."
As always, choice of hardware will vary as time goes on but one must take into account that, unless using large monolithic sample library file architectures, electronic music creation uses samples that involve the continuous reading into memory of 1000s of tiny files. Faster buses, smaller disks (SSDs), and drive optimization are key to avoiding hiccups.
The resulting experience I gained I will relate in four music networking tutorials which I post here on my LBRY channel: 1) "How I built my own server-class music workstation," 2) "How to network music workstations together," and 3) "Sibelius as scoring editor," and 4) "Sibelius as scoring editor - Part 2."
As always, choice of hardware will vary as time goes on but one must take into account that, unless using large monolithic sample library file architectures, electronic music creation uses samples that involve the continuous reading into memory of 1000s of tiny files. Faster buses, smaller disks (SSDs), and drive optimization are key to avoiding hiccups.
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