Projects

SHAKTIMAAN : An open-source DNN accelerator

Advisor: Prof. Pratyush Kumar

Jun 2019 - May 2020

• Architected a systolic-array based DNN accelerator
• co-processor to SHAKTI processor

Cache coherence protocol for Shakti C-Class processor

Advisor: Prof. Kamakoti

Summer 2018, Spring 2019

Implemented cache-coherence protocol for multi-core SHAKTI processor

• MOESI protocol
• Both snoop-based (Summer 2018) and directory-based (Spring 2019)

Efficient convolution on GPUs by exploiting Quantization

Advisor: Prof. Pratyush Kumar

Fall 2018

Implemented CUDA kernels to efficiently perform convolution in GPUs by Quantization. In quantized convolutional filter maps, weight values are redundant and can be shared, thereby reducing memory used. Overall, it was found that weight sharing did not provide any speedup over baseline model, owing to increase in book-keeping instructions needed for execution of convolution.