The company’s Blaize Graph Streaming Processor (GSP) architecture is claimed to be the first to enable concurrent execution of multiple neural networks and entire workflows on a single system, while supporting a diverse range of heterogeneous compute intensive workloads. The startup says its fully programmable solution brings new levels of flexibility for evolving AI models, workflows, and applications that run efficiently where needed.
“Blaize was founded on a vision of a better way to compute the workloads of the future by rethinking the fundamental software and processor architecture,” said Dinakar Munagala, Co-founder and CEO, Blaize. “We see demand from customers across markets for new computing solutions that address the immediate unmet needs for technology built for the emerging age of AI, and solutions that overcome the limitations of power, complexity and cost of legacy computing.”
Unlike single-function ASICs designed for AI, the GSP is meant to be more general purpose to reach many markets, from automotive to the edge to the cloud. The Blaize GSP architecture together with the Blaize Picasso software development platform blend dynamic data flow methods and graph computing models with fully programmable proprietary SOCs.