DAC’24: Implementation of Redundancy-Free Recommendation Model Training Based on Reusable-Aware Near-Memory Processing
In recent years, recommendation systems have played an increasingly important role across various industries. Among them, the embedding layer of recommendation systems has become a performance bottleneck due to the large volume of data and irregular memory access patterns. Existing works utilize the data locality of the embedding layer to cache frequently accessed embedding vectors … Read more