PacQ introduces a novel SIMT microarchitecture designed to optimize the inherent asymmetry in quantized large language models where weights are stored in low-precision integers while activations remain in full-precision floating-point format.

• Addresses the computation bottleneck in hyper-asymmetric GEMMs (General Matrix Multiplications)
• Leverages packaged computation units to efficiently process mixed-precision operations
• Achieves significant performance improvements for LLM inference while maintaining accuracy
• Provides a hardware-specific solution for the growing deployment needs of quantized LLMs

This research matters for engineering teams deploying LLMs at scale, offering a specialized hardware architecture that can significantly reduce computational overhead without sacrificing model performance.

PacQ: A SIMT Microarchitecture for Efficient Dataflow in Hyper-asymmetric GEMMs