Web search engines are facing formidable performance challenges as they need to process thousands of queries per second over billions of documents. To deal with this heavy workload, current engines use massively parallel architectures of thousands of machines that require large hardware investments. We investigate new ways to build such high-performance IR systems based on Graphical Processing Units (GPUs). GPUs were originally designed to accelerate computer graphics applications through massive on-chip parallelism. Recently a number of researchers have studied how to use GPUs for other problem domains including databases and scientific computing [2, 3, 5], but we are not aware of previous attempts to use GPUs for large-scale web search. Our contribution here is to design a basic system architecture for GPU-based high-performance IR, and to describe how to perform highly efficient query processing within such an architecture. Preliminary experimental results based on a prototype implementation suggest that significant gains in query processing performance might be obtainable with such an approach.