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of 25
pro vyhledávání: '"Karempudi, Venkata Sai Praneeth"'
Autor:
Karempudi, Venkata Sai Praneeth, Vatsavai, Sairam Sri, Thakkar, Ishan, Alo, Oluwaseun Adewunmi, Hastings, Jeffrey Todd, Woods, Justin Scott
Over the past few years, several microring resonator (MRR)-based analog photonic architectures have been proposed to accelerate general matrix-matrix multiplications (GEMMs), which are found in abundance in deep learning workloads.These architectures
Externí odkaz:
http://arxiv.org/abs/2402.11047
Several photonic microring resonators (MRRs) based analog accelerators have been proposed to accelerate the inference of integer-quantized CNNs with remarkably higher throughput and energy efficiency compared to their electronic counterparts. However
Externí odkaz:
http://arxiv.org/abs/2402.03247
Autor:
Vatsavai, Sairam Sri, Karempudi, Venkata Sai Praneeth, Alo, Oluwaseun Adewunmi, Thakkar, Ishan
Several microring resonator (MRR) based analog photonic architectures have been proposed to accelerate general matrix-matrix multiplications (GEMMs) in deep neural networks with exceptional throughput and energy efficiency. To implement GEMM function
Externí odkaz:
http://arxiv.org/abs/2402.03149
In the wake of dwindling Moore's Law, to address the rapidly increasing complexity and cost of fabricating large-scale, monolithic systems-on-chip (SoCs), the industry has adopted dis-aggregation as a solution, wherein a large monolithic SoC is parti
Externí odkaz:
http://arxiv.org/abs/2306.07241
The use of the Silicon-on-Insulator (SOI) platform has been prominent for realizing CMOS-compatible, high-performance photonic integrated circuits (PICs). But in recent years, the silicon-nitride-on-silicon-dioxide (SiN-on-SiO$_2$) platform has garne
Externí odkaz:
http://arxiv.org/abs/2306.07238
In this paper, we present microring resonator (MRR) based polymorphic E-O circuits and architectures that can be employed for high-speed and energy-efficient non-binary reconfigurable computing. Our polymorphic E-O circuits can be dynamically program
Externí odkaz:
http://arxiv.org/abs/2304.07608
Autor:
Vatsavai, Sairam Sri, Karempudi, Venkata Sai Praneeth, Thakkar, Ishan, Salehi, Ahmad, Hastings, Todd
The acceleration of a CNN inference task uses convolution operations that are typically transformed into vector-dot-product (VDP) operations. Several photonic microring resonators (MRRs) based hardware architectures have been proposed to accelerate i
Externí odkaz:
http://arxiv.org/abs/2302.07036
Binary Neural Networks (BNNs) are increasingly preferred over full-precision Convolutional Neural Networks(CNNs) to reduce the memory and computational requirements of inference processing with minimal accuracy drop. BNNs convert CNN model parameters
Externí odkaz:
http://arxiv.org/abs/2302.06405
Autor:
Karempudi, Venkata Sai Praneeth, Vatsavai, Sairam Sri, Thakkar, Ishan, Hastings, Jeffrey Todd
In the wake of dwindling Moore's law, integrated electro-optic (E-O) computing circuits have shown revolutionary potential to provide progressively faster and more efficient hardware for computing. The E-O circuits for computing from the literature c
Externí odkaz:
http://arxiv.org/abs/2301.13626
The use of the Silicon-on-Insulator (SOI) platform has been prominent for realizing CMOS-compatible, high-performance photonic integrated circuits (PICs). But in recent years, the silicon-nitride-on-silicon-dioxide (SiN-on-SiO$_2$) platform has garne
Externí odkaz:
http://arxiv.org/abs/2212.06326