Originally posted to Data Center Frontier by Rich Miller.
The artificial intelligence arms race continues, as the largest tech companies explore new ways accelerate AI workloads for cloud platforms. The appetite for more computing horsepower is following several tracks, with major investment in graphics processors (GPUs) as well as custom ASIC chips.
Microsoft has been a leader in using FPGAs (Field Programmable Gate Arrays) to accelerate its cloud and AI workloads. This week Microsoft unveiled Project Brainwave, a deep learning acceleration platform based on its collaboration with Intel on FPGA computing.
Microsoft says Project Brainwave represents a “major leap forward” in cloud-based deep learning performance, and intends to bring the technology to its Windows Azure cloud computing platform.
“We designed the system for real-time AI, which means the system processes requests as fast as it receives them, with ultra-low latency,” writes Doug Burger, a Microsoft Distinguished Engineer, in a blog post. “Real-time AI is becoming increasingly important as cloud infrastructures process live data streams, whether they be search queries, videos, sensor streams, or interactions with users.
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