3 papers
cs.AR2025
DABench-LLM: Standardized and In-Depth Benchmarking of Post-Moore Dataflow AI Accelerators for LLMs
Ziyu Hu, Zhiqing Zhong, Weijian Zheng +6
The exponential growth of large language models has outpaced the capabilities of traditional CPU and GPU architectures due to the slowdown of Moore's Law. Dataflow AI accelerators…
cs.AR2024
GFormer: Accelerating Large Language Models with Optimized Transformers on Gaudi Processors
Chengming Zhang, Xinheng Ding, Baixi Sun +4
Heterogeneous hardware like Gaudi processor has been developed to enhance computations, especially matrix operations for Transformer-based large language models (LLMs) for generati…
cs.LG2023
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors
Chengming Zhang, Baixi Sun, Xiaodong Yu +5
Transformer models have achieved remarkable success in various machine learning tasks but suffer from high computational complexity and resource requirements. The quadratic complex…