4 papers
TokenButler: Token Importance is Predictable
Yash Akhauri, Ahmed F AbouElhamayed, Yifei Gao +4
Large Language Models (LLMs) rely on the Key-Value (KV) Cache to store token history, enabling efficient decoding of tokens. As the KV-Cache grows, it becomes a major memory and co…
BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration
Yuzong Chen, Ahmed F. AbouElhamayed, Xilai Dai +4
Large language models (LLMs) have demonstrated remarkable performance across various machine learning tasks. Yet the substantial memory footprint of LLMs significantly hinders thei…
SplitReason: Learning To Offload Reasoning
Yash Akhauri, Anthony Fei, Chi-Chih Chang +3
Reasoning in large language models (LLMs) tends to produce substantially longer token generation sequences than simpler language modeling tasks. This extended generation length ref…
SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs
Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri +6
Large language models have high compute, latency, and memory requirements. While specialized accelerators such as GPUs and TPUs typically run these workloads, CPUs are more widely…