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Explore methods to optimize LLM inference on RISC-V architecture, focusing on performance bottlenecks in quantized models.

VectorWeaver: A Stage-Aware Automated Optimization Framework for LLM Inference on Edge Platform

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This automated framework enhances LLM inference performance on edge platforms, suggesting new optimization strategies for AI hardware.

Explore methods to optimize LLM inference on RISC-V architecture, focusing on performance bottlenecks in quantized models.
Developed an automated framework named VectorWeaver
Implemented a stage-aware performance model
Explored optimization strategies like loop unrolling and software pipelining
Generated optimized microkernels for prefill and decode stages
Achieved up to a 24x speedup in microkernel performance against baseline implementations
Delivered a 5.2x increase in inference throughput
Successfully automated high-performance code generation for LLM inference on RISC-V

Yang et al. (2026) studied this question.

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