Dally develops efficient hardware for demanding information processing problems and sustainable energy systems. His current projects include domain-specific accelerators for deep learning, bioinformatics, and SAT solving; redesigning memory systems for the data center; developing efficient methods for video perception; and developing efficient sustainable energy systems. His research involves demonstrating novel concepts with working systems. Previous systems include the MARS Hardware Accelerator, the Torus Routing Chip, the J-Machine, M-Machine, the Reliable Router, the Imagine signal and image processor, the Merrimac supercomputer, and the ELM embedded processor. His work on stream processing led to GPU computing. His group has pioneered techniques including fast capability-based addressing, processor coupling, virtual channel flow control, wormhole routing, link-level retry, message-driven processing, deadlock-free routing, pruning neural networks, and quantizing neural networks.