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Neurawave

neurawave

Neurawave is the next generation of QCi’s reservoir computing technology, using a full electro-optic platform optimized for machine learning problems. The Neurawave scales the reservoir computing architecture demonstrated in our commercially-used and published EmuCore system into a high-bandwidth electro-optic platform capable of achieving microsecond latency and real-time streaming performance not available on FPGA or GPU platforms, in a form factor comparable in size to a standard GPU system.

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Capabilities and applications

Our electro-optical analog machine learning hardware is built for AI on the edge:

Signal prediction

Time-series classification

Medical diagnostic signal analysis

Specifications

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Form Factor

PCIe 3.0 form factor with x4 PCIe lanes, 3 slots of PCIE

ADC Sampling Rate

1.25 GSps with a 14-bit resolution

DAC Sampling Rate

1.25 GSps with a 16-bit resolution

Max Nodes

10,000 (1.6 km fiber in 1st prototype)

Throughput

2.5 GB/s over PCIe

Power Consumption

~36 W

Dimensions (L x W x H)

390 mm x 130 mm x 55.5 mm

Weight

1.87 kg

Software Interface

Python API

Development Environment

Compatible with NumPy, PyTorch (for data prep), and standard scientific Python tools.