Techila and Google bring an on-demand supercomputer to every desk


Techila Technologies releases a new on-demand solution that cuts simulation and analysis time from hours to minutes, without the cost and complexity of traditional high-performance computing (HPC).

Techila, the big compute solution, is available globally on Google Cloud Launcher, the online marketplace created and operated by Google Cloud Platform.

“The Techila user experience available in Google Cloud Launcher revolutionizes simulation and analysis. Techila’s patented end-to-end solution integrates the scalable power of Google Cloud Platform seamlessly into popular tools and environments on the user’s own PC: MATLAB, Python, R programming language, and more,” says Rainer Wehkamp, CEO, Techila Technologies Ltd.

Business, research and product development rely heavily on computation in its many forms. Techila is a secure solution that is trusted by industry; central and national banks, leading investment banks, asset managers, and insurance companies. Available in Google Cloud Launcher, Techila makes fast computing available to anyone, anywhere. The user can buy Techila using a Google account on-demand and pay per use.

”Techila enables the timely solution of even the most challenging and complex problems with simplicity, and turning data into rich analytical insights, ” says Rainer Wehkamp.

Techila accelerates time-to-market by enabling interactive computing with uncompromised results. Combining 1000 CPU cores from the Google Cloud Platform with Techila’s technology allows a MATLAB application to run nearly 1000 times faster. The user can save almost 3 days of time at only $10.

“In our use-case, Techila enables efficient analysis of High-Frequency Financial Data. The solution has made it possible to run complex MATLAB algorithms rapidly and simply. I already have my eyes on the next biggest Big Data in Finance problems. Along with the on-demand cloud computing power of Google Cloud Platform Techila is an exciting solution that can enable simulations and analyses that were not possible before, ” says Associate Professor Kim Christensen, Big Data Finance, CREATES, Aarhus University.

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