How Granulate Supports Intel’s High-Performance Computing Efforts

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In its latest move to enable high-performance computing for enterprises, Intel has brought in Israel-based company Granulate, a startup that uses AI to optimize workloads in real time.

The deal, reportedly valued at $650 million, will provide a major boost to the chip giant’s portfolio of optimization tooling that ensures its architecture delivers maximum value when dealing with today’s challenging computing requirements in both cloud and on-premises environments. premises environments.

“Granulate’s innovative approach to real-time optimization software complements Intel’s existing capabilities by helping customers achieve performance improvements, cloud cost savings and continuous workload learning,” said Greg Lavender, CTO, senior vice president and general manager from Intel’s software and advanced technology group. †

So, what does Granules do?

Granulate’s platform uses algorithmic models to learn specific application usage patterns and data flows, and identifies disputed resources, bottlenecks, and prioritization opportunities to work on. Once this process is complete, it uses all of the collected information and makes operating system-level scheduling and resource management decisions to improve application-specific infrastructure performance.

“The Optimizer takes four days to learn the application data flow and processing stages, then, once activated, optimizes resource management decisions,” Asaf Ezra, co-founder and CEO of Granulate, previously told VentureBeat. As part of this, it works on aspects such as memory allocation, process switching, cache, and thread scheduling, among others.

GranulateGranulate’s dashboard.

The whole process works without human intervention or code change and immediately improves performance in terms of cost, throughput and latency. Many companies, including PicsArt, Coralogix, Nativo, and Singular, have already reaped these benefits by signing up for Granulate. The solution’s software agents can be installed on any Linux server in data centers or cloud environments, including virtual machines.

The Intel Association

Intel, for its part, has been closely associated with Granulate since its inception. The startup was the inaugural member of Intel Ignite, an accelerator formed by the chipmaker to create and support select groups of promising start-up companies.

During this program, Granulate worked closely with Intel to demonstrate how its solution improves the performance of 2nd Gen Intel Xeon Scalable Processors when handling key Java-based business software workloads. Then, building on that work, the companies introduced a commercial workload optimizer as part of Intel’s cloud optimization and management tools.

This offering delivered exactly what Granulate promised (performance gains and lower costs), but only for enterprise customers who rely on Intel’s Xeon implementations.

Mobileye, an Intel subsidiary that deployed the optimizer in its hybrid cloud environment, saw a whopping 45% faster job completion and a 44.5% reduction in cloud instance costs. In some cases, the solution can even increase throughput by 5 times, while cutting costs by up to 60%, the company said.

Full stack optimization

With the deal closing in Q2 2022, Intel will look to continue the work it’s done with Granulate on workload optimizer, scaling it and bringing it to more enterprises across its data center and cloud portfolio.

“Together with Intel, we believe we can help customers achieve meaningful cost savings and five times the throughput across a variety of workloads,” said Ezra. He also indicated that the offering will expand under Intel’s umbrella, but did not share specific details.

Gregg Siegfried, vice president, analyst for Gartner’s I&O monitoring team, said the move gives Intel a strong portfolio of tools to optimize at the CPU, operating system, cluster and application levels and ensure workloads running on its platforms. show superior performance.

“Working at the operating system level, Granulate can continuously optimize the Linux kernel to maximize the performance of a workload at any given time, which can significantly benefit public cloud service users by requiring aggregated resources – particularly in consult with the Densify-based Intel Cloud Optimizer (also part of cloud optimization and management tools),” he said.

On the application layer, there is an Intel Ventures company called AIOBench, which deals with the optimization of application workloads through benchmarking. For CPU, tools such as Performance Maximizer and Turbo Boost improve performance chips in view of the specific workloads of gaming – where overclocking is common – and real-time or embedded applications.

“Currently, AI-driven workflow orchestration space includes Turbonomic (IBM), Virtana, Densify, as well as newer players like Sedai and the aforementioned AIOBench. Not all of these are suitable for every workload or application, but being able to optimize for cost in some cases and in others across multiple layers of the stack using Intel-branded tools certainly keeps the Intel platform attractive to both cloud providers and developers’ , remarked Siegfried.

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