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Microsoft has selected Intel Stratix 10 FPGAs as a key hardware accelerator in its new accelerated deep learning platform, code-named Project Brainwave.
The FPGA-based accelerated deep learning platform is capable of delivering “realtime AI”, which will allow cloud infrastructure to process and transmit data as fast as it comes in, with ultralow latency.
In the cloud, delivering real-time AI is becoming more important as systems are required to process live data streams, including video, sensors or search queries, and rapidly deliver the data back to users.
Microsoft was the first major cloud service provider to deploy FPGAs in its public cloud infrastructure and the technology advancements it has demonstrated with Intel Stratix 10 FPGAs enable the acceleration of deep neural networks (DNNs) that replicate “thinking” in a manner that is conceptually similar to that of the human brain.
AI is a rapidly evolving field that requires multiple technologies to efficiently manage various workload requirements. Intel offers a broad set of technologies to enable the market’s evolution, including Intel Xeon processors, Intel FPGAs and Intel Nervana ASIC technology.
Compared to dedicated deep learning hardware accelerators that are optimised to run a single workload, the flexibility of Intel FPGAs enable users to customize the hardware to meet specific workload requirements, and reconfigure the hardware rapidly as deep learning workloads and use models change. Intel Stratix 10 FPGAs combine hardened processor blocks that deliver high levels of sustained performance and efficiency, with a programmable fabric for user customization.
Many silicon AI accelerators today require grouping multiple requests together (called “batching”) to achieve high performance. Project Brainwave, leveraging the Intel Stratix 10 technology, demonstrated over 39 teraflops of achieved performance on a single request, setting a new standard in the cloud for realtime AI computation.
Stratix 10 FPGAs sets a new level of cloud performance for realtime AI computation, with record low latency, record performance and batch-free execution of AI requests.
“We exploit the flexibility of Intel FPGAs to incorporate new innovations rapidly, while offering performance comparable to, or greater than, many ASIC-based deep learning processing units,” says Doug Burger, distinguished engineer at Microsoft Research NExT.
Microsoft is currently working to deploy Project Brainwave in the Azure cloud so that customers eventually can run complex deep learning models at record-setting performance.