Ameya Patil

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It is well-known that the precision of data, hyperparameters, and internal representations employed in learning systems directly impacts their energy, throughput, and latency. The precision requirements for the training algorithm are also important for systems that learn on-the-fly. Prior work has shown that the data and hyperparameters can be quantized(More)
This paper describes a multi-functional deep in-memory processor for inference applications. Deep in-memory processing is achieved by embedding pitch-matched low-SNR analog processing into a standard 6T 16KB SRAM array in 65 nm CMOS. Four applications are demonstrated. The prototype achieves up to 5.6X (9.7X estimated for multi-bank scenario) energy savings(More)
A variety of vision ailments are indicated by structural changes in the retinal substructures of the posterior segment of the eye. In particular, integrity of the inner-segment/outer-segment (IS/OS) junction directly relates to the visual acuity. In the en-face optical coherence tomography (OCT) image, IS/OS damage manifests as a dark spot in the foveal(More)
Structural changes in the choroid, a layer located between the retina and sclera, could indicate various vision impairments. Consequently, ophthalmologists inspect optical coherence tomography (OCT) scans of the posterior section of the eye towards making diagnosis. With a view to assist diagnosis, we propose an automated technique for segmentation of the(More)
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