Donald Bren School of Information and Computer Sciences

We present High-level Library Mapping (HLLM), a technique that permits reuse of complex RT-level databook components (specifically ALUs). HLLM can be used to couple existing databook libraries, module generators and custom-designed components with the output of architectural or behavioral synthesis. In this report, we define the problem of high-level library mapping, present several algorithmic formulations for HLLM of ALUs, and demonstrate the versatility of our approach on a variety of libraries. We also compare HLLM against the traditional mapping approach using logic synthesis. Our experiments show that HLLM for ALUs outperforms logic-synthesis in area, delay and runtime, indicating that HLLM is a promising approach for reuse of datapath components in architectural design and high-level synthesis.