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Hazelcast MapReduce on GPU

April's Fool: Make use of massively scalable GPU power

APRIL'S FOOL:
Sorry that I have to admit it was just an April's Fool. The interesting fact btw is that when I first came up with the idea it sounded like totally implausible but while writing I realized "hey that should actually be possible". Maybe not yet for a map-reduce framework but definitely to back up a distributed fractal calculation what is I will look into at the next time. If somebody want to team up on this I'm fully open for requests. Just don't hesitate to contact me.
While this was a prank at the current time, I'm really looking forward to eventually bring distributed environments like Hazelcast to the GPU - at least when Java 9 will feature OpenJDK Project Sumatra and a big thanks to the guys from AMD and Rootbeet that started all that movement!

Since the last decade RAM and CPU always got faster but still some calculations can be done faster in GPUs due to their nature of data. At Hazelcast we try to make distributed calculations easy and fast for everybody.

While having some spare time I came up with the idea of moving data calculations to the GPU to massively scale it out and since I created the map-reduce framework on the new Hazelcast 3.2 version it was just a matter of time to make it working with a GPU.

Disclaimer: Before you read on I want to make sure that you understand that this is neither an official Hazelcast project nor it is yet likely to be part of the core in the near future but as always you may expect the unexpected!

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Categories : Java, hazelcast