CORDIS Project
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This project focuses on enhancing the efficiency of matrix multiplication, a key operation in artificial intelligence applications. By developing new methods for both software and hardware implementations, it aims to significantly reduce the time and energy required for these computations.
Matrix multiplication consumes huge amount of resources: computing time and energy, primarily in AI applications.
The industry has recognized the need for faster and more energy-efficient matrix multiplication with state-of-the-art solutions in software (e.g., DGEMM of Intel's math kernel library (MKL) for CPU and NVIDIA's CUDA for GPU) and hardware (e.g., Google's TPU and Intel / Habana labs Gaudi accelerator).
Unfortunately, all present solutions employ a wasteful cubic-time algorithm.
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