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Allinea Software Blog

Fri December 16, 2016 by David Lecomber

ARM acquires Allinea: The exciting road ahead

It’s with great excitement that we’re announcing that Allinea is now a part of ARM.

For over 10 years at Allinea we’ve been on an incredible journey to be your cross-platform tools provider for high performance computing (HPC).

It’s a journey that we continue to enjoy sharing: we love working with developers, scientists and engineers, and with educators and researchers, who share our passion for the software and solving some of the harder challenges of supercomputing.

We’re now ready to take another leap forward with you.

What’s new?

Allinea will integrate with the ARM HPC compiler and libraries engineering teams to become a new HPC Tools team within ARM’s Development Solutions Group.

HPC is special to us, and we know it’s special to you. As the HPC Tools team, we’ll continue to serve...

Wed February 8, 2017 by Mark O'Connor, Director Product Management, Server & HPC Tools, ARM
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Last summer we announced Knights Landing support in Allinea Forge and Performance Reports and CUDA support on the OpenPOWER platform. 

Thu October 20, 2016 by Mark O'Connor

In the previous post we parallelized Andrej Karpathy's policy gradient code to see whether a very simple implementation coupled with supercomputer speeds could learn to play Atari Pong faster than the state-of-the-art (DeepMind's A3

Wed October 19, 2016 by Mark O'Connor

I’ve always enjoyed playing games, but the buzz from writing programs that play games has repeatedly claimed months of my conscious thought at a time. I’m not sure that writing programs that write programs that play games is the perfect solution, but I do know that I can never resist it.

Wed August 3, 2016 by Mark O'Connor

In episode one we optimized Torch A3C performance on the new Intel Xeon Phi (Knight's Landing) CPU. Allinea MAP and Performance Reports identified bottlenecks in our framework and sped up model training by 7x.

Thu July 21, 2016 by David Lecomber

The Manufacturing industry relies on high performance software for improving the speed and efficiency with which it brings new or improved products to market.

Tue July 5, 2016 by Mark O'Connor

In February, a new paper from Google's DeepMind team appeared on arxiv. This one was interesting – they showed dramatically improved performance and training time of their Atari-playing Deep Q-Learning network. The training speedup was so great that 16 CPU cores outperformed their previous GPU results by an order of magnitude.