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SYSTEM AND METHOD FOR SYNTHETIC-MODEL-BASED BENCHMARKING OF AI HARDWARE
SYSTEM AND METHOD FOR SYNTHETIC-MODEL-BASED BENCHMARKING OF AI HARDWARE
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机译:基于合成模型的人工智能硬件标记的系统和方法
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摘要
Embodiments described herein provide a system for facilitating efficient benchmarking of a piece of hardware configured to process artificial intelligence (AI) related operations. During operation, the system determines the workloads of a set of AI models based on layer information associated with a respective layer of a respective AI model. The set of AI models are representative of applications that run on the piece of hardware. The system forms a set of workload clusters from the workloads and determines a representative workload for a workload cluster. The system then determines, using a meta-heuristic, an input size that corresponds to the representative workload. The system determines, based on the set of workload clusters, a synthetic AI model configured to generate a workload that represents statistical properties of the workloads on the piece of hardware. The input size can generate the representative workload at a computational layer of the synthetic AI model.
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