We wrote a lot of that stack ourselves. And our compute code is in c++. There is a lot of stuff going on in big data land (including us) wrapping a lot of the c

We wrote a lot of that stack ourselves. And our compute code is in c++. There is a lot of stuff going on in big data land (including us) wrapping a lot of the c++ in java and enabling people to use the JVM for what it's good at (data access). We are pushing this with nvidia: https://blogs.nvidia.com/blog/2016/10/06/how-skymind-nvidia-deep-learning/ https://blogs.nvidia.com/blog/2016/10/06/how-skymind-nvidia-... I also work pretty closely with a lot of the spark/gpu folks at IBM. While I do largely agree with you, we have our own JNI compiler called javacpp that alleviates a lot of those concerns already: https://github.com/bytedeco/javacpp https://github.com/bytedeco/javacpp Having our own pointer class and doing our own memory management has helped a lot. What you're talking about is using java for the compute. There's no reason you can't wrap that in a runtime that most people know how to use. A lot of python folks do that now..but then you have to deal with python's limitations at which point the majority of your code (way more than needs be) will end up being in c anyways vs java where you can write a significant part of your app in java and have it be fast out of the box.