Software giant Microsoft in August 2017 launched its Project Brainwave, which is deep learning acceleration platform for real-time artificial intelligence (AI).
Microsoft has launched the project during the time when real-time artificial intelligence is becoming increasingly important as cloud infrastructures process live data streams, whether they be search queries, videos, sensor streams, or interactions with users.
Key highlights
• The Project Brainwave uses the massive Field-Programmable Gate Array (FPGA) infrastructure that Microsoft has been deploying over the past few years.
• By attaching high-performance FPGAs directly to the data centre network, DNNs can be served as hardware microservices, where a DNN can be mapped to a pool of remote FPGAs and called by a server with no software in the loop.
• The system architecture reduces latency, since the CPU does not need to process incoming requests, and allows very high throughput, with the FPGA processing requests as fast as the network can stream them.
• The system has been architected to yield high actual performance across a wide range of complex models, with batch-free execution.
• The system can handle complex, memory-intensive models such as Long Short Term Memories (LSTM), without using batching to juice throughput.
• Project Brainwave achieves unprecedented levels of demonstrated real-time AI performance on extremely challenging models.
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