1 citations · 2 across the 8 of their papers we have counts for
3 papers · 1 filter
ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models
Akshat Ramachandran, Marina Neseem, Charbel Sakr +3
The long-output context generation of large reasoning models enables extended chain of thought (CoT) but also drives rapid growth of the key-value (KV) cache, quickly overwhelming…
Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator
Akshat Ramachandran, Souvik Kundu, Arnab Raha +3
Large language model (LLM) pruning with fixed N:M structured sparsity significantly limits the expressivity of the sparse model, yielding sub-optimal performance. In contrast, supp…
AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations
Jamin Seo, Akshat Ramachandran, Yu-Chuan Chuang +2
Design space exploration (DSE) plays a crucial role in enabling custom hardware architectures, particularly for emerging applications like AI, where optimized and specialized desig…