SongKong Jaikoz

SongKong and Jaikoz Music Tagger Community Forum

CPU multi-core & multi-thread

Hi guys.
First of all, I haven’t found any “SEARCH” button near here… sorry if the topic still exist; coming to the question: I’ve read all the manual and I don’t know if I’ve left it or if there isn’t trace.

How does Jailkoz use the modern 2 or more core and many threads of ours Macs/PCs? Any way to optimize it, like the RAM option??
Thank in advance.

Michele B.
“OmniMac - Shop with iStyle”

[quote=OmniMac]Hi guys.
First of all, I haven’t found any “SEARCH” button near here… sorry if the topic still exist; coming to the question: I’ve read all the manual and I don’t know if I’ve left it or if there isn’t trace.
[/quote]
At the top under the title there is a Search button

Jaikoz is multi-threaded and makes use of multiple cpus when song matching, you can also increase the RAM available and this is detailed in the manual/help.

But I think you are asking me how can I make Jaikoz work faster ?

Currently Jaikoz talks directly to the MusicBrainz server to find matches, but there are two main problems with this approach.

1:MusicBrainz limits any user from making more than one call per second (rate limit)
2:MusicBrainz Api is not optimized for Jaikoz so I have to make more calls than I would ideally like to get the information I need and I have to download information I don’t need or want.

I’ve been working on JThink Music Server for some time this contains copies of the MusicBrainz and Discogs databases and is regularly updated. The data and the api is optimized to return exactly what Jaikoz needs in the minimal amount of calls and runs on my server where I can control the rate limit. This solves problem 1 & 2.

JThinkMusicServer is already used by SongKong and will be used in the next release of Jaikoz whihc will definently be released next week and typically has performance improvements of 1000 %

Michele B.
“OmniMac - Shop with iStyle”[/quote]

A new version you say?

Well I may hold off my tidy up of genres that I was about to do.