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News Announcements

Concertio Awarded with PowerBridgeNY Ignition Grant

Concertio Optimizer is a great tool for improving performance of servers with minimum engineering effort. In addition to boosting performance, Concertio Optimizer is also able to improve the energy efficiency of servers by optimizing for performance per Joule. We...

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Media Coverage

This NYC Startup Uses AI to Optimize Your Servers

A company’s technology stack functions much like an orchestra; many parts working together in harmony, but if one instrument is too slow or out of tune, the entire company runs less effectively. Concertio, previously known as DatArcs, serves as an AI-driven maestro that optimizes and orchestrates your software and hardware deployments. When deploying and maintaining your server, there are a myriad of options that can be configured and optimizing this architecture across your technology stack ensures that the show runs smoother.
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Podcast: Machine Learning for Auto-Tuning HPC Systems

While the role of performance engineer will not disappear anytime soon, machine learning is making tuning systems—everything from CPUs to application specific parameters—less of a burden. Despite the highly custom nature of systems and applications, reinforcement learning is allowing new leaps in time-saving tuning as software learns what works best for user applications and architectures, freeing up performance engineers to focus on the finer points of system behavior.
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Startup Concertio offers AI-optimized server configuration

AI-Powered / Machine Learning Linux Performance Tuning Is Now A Thing

A year and a half ago I wrote about a start-up working on dynamically-tuned, self-optimizing Linux servers. That company is now known as Concertio and they just launched their “AI powered” toolkit for IT administrators and performance engineers to optimize their server performance.
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Start-up Aims AI at Automated Tuning of Complex Systems

Today’s bigger, more complex, connected and intelligent systems have an exponentially higher number of connections, dependencies, interfaces, protocols and processing architectures that, if not optimized, will hamstring performance. For performance engineers still using manual tuning methods, systems optimization is a time-eating hydra-headed monster that poses a virtually infinite number of possible adjustments and configurations for trial-and-error testing. Enter AI.
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Start-up Aims AI at Automated Tuning of Complex Systems

There was a simpler time when system tuning consisted of adjusting a relatively few number of knobs, a manual and not overly demanding task that brought out the best in systems performance. But now, as we move toward accelerated enterprise systems networked from data center to public cloud to mobile and sensored devices at the edge, simplicity in systems tuning is long gone.
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