Domain-Specific Processor with 3D Integration for Medical Image Processing

The growth of 3D technology had led to opportunities for stacked multiprocessor-accelerator computing platforms with high-bandwidth and low-latency TSV connections between them, resulting in high computing performance and better energy efficiency. This work evaluates the performance and energy benefits of such an advanced architecture and addresses associated design problems. To better utilize the reconfigurable hardware resource and to explore the opportunity of kernel sharing across applications, we propose to use a dedicated domain-specific computing platform. In particular, we have chosen medical image processing as the domain in this work to accelerate due to its growing for real-time processing demand yet inadequete performance on conventional computing architectures. A design flow is proposed in this work for the 3D multiprocessor-accelerator platform and a number of methods are applied to optimize the average performance of all the applications in the targeted domain under area and bandwidth constraints. Experiments show that the applications in this domain can gain a 7.4x speed-up and 18.8x energy savings on average running on our platform using CMP cores and domain-specific accelerators as compared to their counterparts coded in CPU only.