<ul data-eligibleForWebStory="false"><li>Transposed Convolutions (TCONV) play a key role in generative Artificial Intelligence (AI) models for up-scaling.</li><li>Efforts are being made to address inefficiencies in implementing TCONV on resource-constrained edge devices.</li><li>MM2IM, a hardware-software co-designed accelerator combining MatMul with col2IM, is proposed to efficiently process TCONV layers.</li><li>MM2IM shows significant performance improvements, achieving speedups in processing TCONV layers compared to CPU baselines and other accelerators.</li></ul>

Accelerating Transposed Convolutions on FPGA-based Edge Devices

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