A new article, by Brian Bailey in Semiconductor Engineering: “Software-Hardware Co-Design Becomes Real.”

Bailey writes:

  • “Impact of AI: The rapid development of AI has flipped the focus from a hardware-first to a software-first flow. “Understanding AI and ML software workloads is the critical first step to beginning to devise a hardware architecture,” says Lee Flanagan, CBO for Esperanto Technologies. “Workloads in AI are abstractly described in models, and there are many different types of models across AI applications. These models are used to drive AI chip architectures. For example, ResNet-50 (Residual Networks) is a convolutional neural network, which drives the needs for dense matrix computations for image classification. Recommendation systems for ML, however, require an architecture that supports sparse matrices across large models in a deep memory system.””
  • “Coming together: It is unlikely that a pure hardware-first or software-first approach will be successful long-term. It takes collaboration. “AI applications demand a holistic approach,” says Esperanto’s Flanagan. “This spans everyone from low-power circuit designers to hardware designers, to architects, to software developers, to data scientists, and extending to customers, who best understand their important applications.””

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