Papers by Keivan Alizadeh
LLM in a flash: Efficient Large Language Model Inference with Limited Memory (2024.acl-long)
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Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, S. Khatamifard, Minsik Cho, Carlo C Del Mundo, Mohammad Rastegari, Mehrdad Farajtabar
| Challenge: | Large language models (LLMs) have high computational and memory requirements, especially for devices with limited memory. |
| Approach: | They propose a method that stores model parameters in flash memory but brings them on demand to DRAM . authors propose two techniques to optimize for reading data in larger, more contiguous chunks . |
| Outcome: | The proposed method reduces the volume of data transferred from flash and reads data in larger, more contiguous chunks. |