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Vectorized FlashAttention with Low-cost Exponential Computation in RISC-V Vector Processors
Vasileios Titopoulos, Kosmas Alexandridis, Giorgos Dimitrakopoulos
Attention is a core operation in numerous machine learning and artificial intelligence models. This work focuses on the acceleration of attention kernel using FlashAttention algori…
Custom Algorithm-based Fault Tolerance for Attention Layers in Transformers
Vasileios Titopoulos, Kosmas Alexandridis, Giorgos Dimitrakopoulos
Transformers and large language models (LLMs), powered by the attention mechanism, have transformed numerous AI applications, driving the need for specialized hardware accelerators…
FLASH-D: FlashAttention with Hidden Softmax Division
Kosmas Alexandridis, Vasileios Titopoulos, Giorgos Dimitrakopoulos
The transformer's attention mechanism has revolutionized AI and machine learning, with its efficient computation being crucial to its performance. However, calculating attention in…