Rootbeer GPU Compiler Lets Almost Any Java Code Run On the GPU

I wonder if this is as big a win as it sounds. Regardless of what language you're using, you have to "think GPU" to get any performance from GPUs. The additional overhead of using CUDA/OpenCL syntax seems pretty small in comparison.

I had forgotten just how much I hate java namespaces.<p>import edu.syr.pcpratts.rootbeer.testcases.rootbeertest.serialization.MMult;<p>This seems like a pretty amazing project if the claims are true, though - I wasn't aware that CUDA was able to express so many of the concepts used to implement Java applications. The performance data in the slides is certainly compelling!

It would be good to post the code for the performance tests in the slides. <a href="https://raw.github.com/pcpratts/rootbeer1/master/doc/hpcc_rootbeer.pdf" rel="nofollow">https://raw.github.com/pcpratts/rootbeer1/master/doc/hpcc_ro...</a>

this sort of thing is why NVIDIA is supporting LLVM:<p><a href="http://nvidianews.nvidia.com/Releases/NVIDIA-Contributes-CUDA-Compiler-to-Open-Source-Community-7d0.aspx" rel="nofollow">http://nvidianews.nvidia.com/Releases/NVIDIA-Contributes-CUD...</a><p>in other words, with that and the right frontend, you can take Language X, compile to LLVM IR, and run it through the PTX backend to get CUDA.<p>however, in the grand scheme of things, this probably doesn't make GPU programming significantly easier to your average developer (as you still have to deal with big complicated parallel machines); what it really does is ease integration into various codebases in those different languages.

A comparison with AMD's Java offering, Arapi (<a href="http://developer.amd.com/zones/java/aparapi/pages/default.aspx" rel="nofollow">http://developer.amd.com/zones/java/aparapi/pages/default.as...</a>), would be interesting.

"Rootbeer was created using Test Driven Development and testing is essentially important in Rootbeer"<p>I'm not sure what the "essentially" means here, but this is the first "big" program I'm aware of that name-checks TDD, and a counter-example to my theory that programs where much of the programmer effort goes into algorithms and data structures are not suited to TDD.<p>Was the TDD approach "pure"? (Only one feature implemented at a time, with absolutely no design thought given to what language features might need to be implemented in the future.)

Its pretty cool. Of course you are probably using that GPU in a desktop, but an on die GPU in a server class machine? Something to consider.

Does this simply run your java code on the GPU, or does it parallelize your code automatically? The latter would be really cool.

I prefer programming in CUDA over programming in Java. However, I have a lot of respect for the Java runtime.<p>If Rootbeer or something similar allows me to program CUDA stuff in Clojure, then I am impressed and excited.

Has anybody used Rootbeer with language which compiles to Java bytecode (like Clojure)?<p>It would be interesting to see how functional languages designed for parallelism perform on gpu.

&#62; The license is currently GPL, but I am planning on changing to a more permissive license. My overall goal is to get as many people using Rootbeer as possible.<p>It would be bad to compromise the freedoms of the users in order to be able to limit the freedoms of more of them.<p>Any reason why the GPLv3 would be considered unsuitable? How about the LGPLv3?

The title captured the true character of Java: Write once, almost run almost everywhere.

<p><pre><code> 4. sleeping while inside a monitor. </code></pre> ... Can someone clarify what this is?

Seems much nicer than coding directly for CUDA or OpenCL

At first glance this seems very impressive.

Any security implications? Malware running on the GPU?