Hello Steve, Starting with Apache Ignite 2.0 the project is no longer considered as an in-memory technology only.
The new virtual memory architecture that sits at the core of the platforms allows considering Ignite as an memory-first (memory-optimized) computational platform that distributes data and workloads across a cluster of machines storing it both in RAM and on disk. The off-heap is a primary storage of your data. As for the secondary storage you can use SSDs, Flash, Intel 3DxPoint, etc. I think that GPUs can be integrated with the virtual memory as well going forward. At all, now with Ignite you can gain in-memory performance with durability with disk cluster wide. This is one of the main things we need to keep in mind. — Denis > On Jun 13, 2017, at 6:18 AM, steve.hostettler <[email protected]> > wrote: > > Hello, > > Having to explain the choice of Ignite internally, I wonder what is the > "official" position of Apache Ignite towards Storage Class Memory and using > GPUs. > > On the SCM story, I guess it is just another way of allocating/freeing > memory in a kind of off-heap mode but on disk. > > On the GPUs story, I guess is whether or not a library like jcuda can be > used inside Ignite transparently. > > Could you elaborate on this topics? But I would like to have more details > if possible. > > > Best Regards > > > > -- > View this message in context: > http://apache-ignite-users.70518.x6.nabble.com/Apache-Ignite-Memory-Class-Storage-GPUs-and-all-that-tp13646.html > Sent from the Apache Ignite Users mailing list archive at Nabble.com.
