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cs.CL2025
LLMs Know What to Drop: Self-Attention Guided KV Cache Eviction for Efficient Long-Context Inference
Guangtao Wang, Shubhangi Upasani, Chen Wu +5
Efficient long-context inference is critical as large language models (LLMs) adopt context windows of ranging from 128K to 1M tokens. However, the growing key-value (KV) cache and…
cs.CL2024
Kernel Looping: Eliminating Synchronization Boundaries for Peak Inference Performance
David Koeplinger, Darshan Gandhi, Pushkar Nandkar +9
Token generation speed is critical to power the next wave of AI inference applications. GPUs significantly underperform during token generation due to synchronization overheads at…