Date:11/02/16
Instead of sharing memory, each of the Eyeriss chip's 168 cores received its own discrete memory cache. This avoids porting data around the system, thus increasing the speed.
The new chip design also sports a specially crafted circuit, which is able to compress the information prior to sending it on. Decompression occurs when the data reaches its destination, so data shipping time gets trimmed.
One of the essential features of the chip is its customized circuitry. It spreads the load, thus crunching through more data in the shortest time possible before fetching more from the main memory store.
When an Eyeriss chip is installed in a smartphone, it will negate the need to send data to the cloud for high-power processing of AI algorithms, improving speed, security and the need for a Wi-Fi or data connection. Complex AI tasks will be able to be processed locally, brining machine learning to a handheld device.
New AI chip could bring artificial intelligence to smartphone
Eyeriss, a new 168-core chip, was presented by MIT recently at the International Solid State Circuits Conference in San Francisco. The team of researchers impressed everyone with its deep learning capabilities and ability to run powerful AI algorithms locally. It will be 10 times more powerful as a mobile GPU. Energy friendly, the processor runs AI algorithms locally rather than uploading to the Internet.Instead of sharing memory, each of the Eyeriss chip's 168 cores received its own discrete memory cache. This avoids porting data around the system, thus increasing the speed.
The new chip design also sports a specially crafted circuit, which is able to compress the information prior to sending it on. Decompression occurs when the data reaches its destination, so data shipping time gets trimmed.
One of the essential features of the chip is its customized circuitry. It spreads the load, thus crunching through more data in the shortest time possible before fetching more from the main memory store.
When an Eyeriss chip is installed in a smartphone, it will negate the need to send data to the cloud for high-power processing of AI algorithms, improving speed, security and the need for a Wi-Fi or data connection. Complex AI tasks will be able to be processed locally, brining machine learning to a handheld device.
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