CENTRALE LYON - PhD Silicon Photonics for Scalable Energy-Efficient AI Hardware Accelerators

The rapid expansion of artificial intelligence (AI) applications across cloud and edge environments is driving the need for highly efficient hardware capable of supporting increasingly demanding workloads. Among these, matrix multiplication – particularly General Matrix Multiplication (GEMM) – remains the dominant computational kernel in modern AI models, including deep neural networks and transformer architectures. Conventional electronic accelerators, while highly optimized, face growing chall