DeepLink: a heterogeneous approach to AI computing

China is exploring new ways to increase its computing power in the field of artificial intelligence. DeepLink is one of these, focused on the integration of heterogeneous chips.

The main goal of this technology is to combine available computing resources, even if they come from different architectures, to achieve superior performance. This approach could represent a response to restrictions on access to advanced technologies imposed by other countries.

For those evaluating on-premise deployments, there are trade-offs to consider carefully. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects in detail.

General context

Heterogeneity in AI hardware is a growing trend. Combining CPUs, GPUs, and specialized accelerators (such as FPGAs or ASICs) allows for workload optimization, leveraging the strengths of each architecture. DeepLink seems to aim precisely at this: orchestrating different resources to maximize overall efficiency.