Real-time processor combines higher performance and access to greater memory - The EE

Real-time processor combines higher performance and access to greater memory

In a world of billions of connected devices, data processing can no longer ony happen in the cloud. Computational storage is emerging as a critical piece of the data storage puzzle because it puts processing power directly on the storage device, giving companies secure, quick and easy access to vital information.

Arm has now announced the Cortex-R82, its first 64-bit, Linux-capable Cortex-R processor designed to accelerate the development and deployment of next-generation enterprise and computational storage solutions.

According to Neil Werdmuller, director of storage solutions at Arm, the Cortex-R82 will generate insight where data is stored, creating value across a range of applications, and enabling a faster start for developers. “For processing to take place closer to the data, we needed to deliver higher performance. The new Arm Cortex-R82 provides up to 2x performance uplift, depending on the workload, compared to previous Cortex-R generations.

This will allow storage applications to run new workloads like machine learning at a lower latency, with optional Arm Neon technology to provide additional acceleration. Cortex-R82 is 64-bit, providing access of up to 1TB of DRAM for advanced data processing in storage applications.”

Werdmuller adds, “Storage controllers traditionally run bare-metal/RTOS workloads to store and access data, however Cortex-R82 introduces an optional memory management unit (MMU) to allow for rich operating systems to run directly on the storage controller, creating the opportunity for new and improved applications that will benefit both consumers and businesses.”

“Processing data where it is stored opens huge opportunities across applications including IoT, ML and edge computing. This is critical in the storage use cases you might expect, such as database acceleration, meaning no movement of large files and increased security and privacy, and video transcoding where data can be efficiently transcoded or encoded for streaming, adapting different bit rates and resolutions as necessary. But it’s also increasingly important for applications such as transportation – for example, modern airplanes generate terabytes of data a day that is usually offloaded for analysis. Computational storage offers airlines real-time analysis of this data on the drive, so when a plane lands, they can ensure it’s safe for the next flight in 30 minutes or less, enabling faster turnaround and better safety for passengers,” he says.

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