We present Versatile Inference Processor (VIP), a highly programmable architecture for machine learning inference. VIP consists of 128 lightweight processing engines employing a vector processing paradigm, with a simple ISA and carefully chosen …
Maximum a posteriori probability (MAP) inference on Markov random fields (MRF) is the basis of many computer vision applications. Sequential tree-reweighted belief propagation (TRW-S) has been shown to provide very good inference quality and strong …
Vertex-centric graph computations are widely used in many machine learning and data mining applications that operate on graph data structures. This paper presents GraphGen, a vertex-centric framework that targets FPGA for hardware acceleration of …