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.
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
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. |