We introduce GenMatch, a novel set of techniques based on hardware synthesis, for achieving efficient and scalable privacy-preserving genetic testing. Processing and handling sensitive genome data require methodologies to thwart possible attacks and data theft scenarios. The GenMatch secure genome testing method utilizes Yao’s Garbled Circuit (GC) protocol and creates a formulation of the matching problem in a sequential GC format. Our formulation involves private matching of genome data by the GC protocol. Our method reduces the memory footprint of the secure computation such that it can be done in a resource-constrained devices like embedded platforms, rendering the method scalable and time-efficient. Proofof-concept evaluations are performed on the application of matching Human Leukocyte Antigen (HLA) data for organ and tissue transplant compatibility between recipient and donors. This type of testing also has applications in ancestry testing and genetic matchmaking. HLA data of the recipient is matched with a database of possible donor HLA data while keeping the data from both parties private. Experimental results on real genome data demonstrate the practicability of GenMatch in terms of timing and communication complexity for HLA database in the order of million user profiles.