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La fotónica y las microondas se fusionan para mejorar la flexibilidad informática

Hongwei Wang1, Guangwei Hu2

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Los investigadores desarrollaron una unidad de procesamiento de tensores fotónicos utilizando un resonador de microredes para cálculos eficientes de redes neuronales artificiales. Este chip logra una alta densidad de computación fotónica, superando las limitaciones electrónicas en las operaciones tensoriales.

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Área de la Ciencia:

  • La computación fotónica
  • Redes neuronales artificiales
  • Fotónica integrada

Sus antecedentes:

  • Las redes neuronales artificiales (ANN) se basan en operaciones tensoriales, que son computacionalmente intensivas.
  • Las arquitecturas electrónicas tradicionales se enfrentan a un cuello de botella de almacenamiento y computación, lo que dificulta el procesamiento eficiente de tensores a gran escala.
  • Las soluciones de computación fotónica existentes a menudo carecen de la densidad y la eficiencia requeridas para tareas ANN complejas.

Objetivo del estudio:

  • Desarrollar una nueva unidad de procesamiento de tensores fotónicos (PTPU) para acelerar los cálculos ANN.
  • Para superar las limitaciones de la computación electrónica en el manejo de operaciones tensoriales de alta dimensión.
  • Mejorar la densidad de computación y la eficiencia de los circuitos fotónicos integrados para el hardware de IA.

Principales métodos:

  • Se utilizó un solo resonador de microring como el componente central para el procesamiento de tensores fotónicos.
  • Las operaciones de convolución tensorial se realizaron manipulando múltiples dimensiones: tiempo, longitud de onda y frecuencia de microondas.
  • El control preciso de los láseres de múltiples longitudes de onda permitió el ajuste dinámico del estado de funcionamiento del resonador.

Principales resultados:

  • El PTPU desarrollado ejecutó con éxito operaciones de convolución de tensores multidimensionales.
  • Se logró una notable densidad de cómputo fotónico de 34,04 TOPS/mm2.
  • Esta densidad supera significativamente los parámetros de rendimiento de los chips fotónicos actuales.

Conclusiones:

  • El PTPU basado en microring-resonador ofrece una solución prometedora para el procesamiento eficiente de tensores en las ANN.
  • Este avance aborda el cuello de botella crítico en la computación electrónica para la aceleración de la IA.
  • La alta densidad de computación alcanzada allana el camino para la próxima generación de hardware de IA fotónica de alto rendimiento.