IBM unveils on-chip accelerated AI processor
Called “Telum,” the processor is the company’s first that contains on-chip acceleration for AI inferencing while a transaction is taking place. The breakthrough of this new on-chip hardware acceleration, says the company, is designed to help customers achieve business insights at scale across banking, finance, trading, insurance applications and customer interactions.
Telum is designed to enable applications to run efficiently where the data resides, helping to overcome traditional enterprise AI approaches that tend to require significant memory and data movement capabilities to handle inferencing. With the accelerator in close proximity to mission critical data and applications, enterprises can conduct high volume inferencing for real time sensitive transactions without invoking off platform AI solutions, which may impact performance.
Users can also build and train AI models off-platform, deploy and infer on a Telum-enabled IBM system for analysis. The new chip features a centralized design, which allows users to leverage the full power of the AI processor for AI-specific workloads, making it ideal for financial services workloads like fraud detection, loan processing, clearing and settlement of trades, anti-money laundering and risk analysis.
Each Telum chip contains eight processor cores with a deep super-scalar out-of-order instruction pipeline, running with more than 5 GHz clock frequency, optimized for the demands of heterogenous enterprise class workloads. The completely redesigned cache and chip-interconnection infrastructure provides 32 MB cache per core, and allows users to scale up to 32 chips. The dual-chip module design contains 22 billion transistors and 19 miles of wire on 17 metal layers, says the company.
Three years in development, Telum is the first IBM chip with technology created by the IBM Research AI Hardware Center. In addition, Samsung is IBM’s technology development partner for the Telum processor, developed in 7-nm EUV technology node.
A Telum-based system is planned for the first half of 2022.
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