New DEEP-GAP study compares NVIDIA T4 and L4 GPU inference performance

A new research paper introduces DEEP-GAP, a methodology for evaluating GPU inference performance. The study systematically compares the NVIDIA T4 and L4 GPUs using various deep learning models and precision modes. Results indicate that the L4 GPU offers significantly higher throughput than the T4, particularly at smaller batch sizes, while reduced precision modes like INT8 provide substantial performance gains over CPU baselines. AI

影响 Provides practical guidance for optimizing inference deployments by comparing GPU architectures and precision modes.

排序理由 The cluster contains a new academic paper detailing a novel evaluation methodology for GPU inference performance. [lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

• DEEP-GAP
• Kathiravan Palaniappan
• NVIDIA L4
• NVIDIA T4
• PyTorch
• ResNet101
• ResNet18
• ResNet50
• TensorRT

• 论文
• 基础设施

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