221 citations · 470 across the 37 of their papers we have counts for
38 papers
DCRA: Diffusion-Conditioned Representation Alignment for Robust Time-Series Learning
Wenrui Xu, Anas Enanaa, Keshab K. Parhi
Learning robust representations for time-series signals under noise and distribution shifts remains challenging, especially in clinical applications such as electroencephalogram (E…
Noise-Aware Synthesis of Quantum LDPC Encoder Circuits via Two-Sided Hamming Descent
Aditya Sodhani, Keshab K. Parhi
Quantum low-density parity-check (LDPC) codes are a promising route to fault-tolerant quantum computation, but their use requires efficient preparation of encoded states. Standard…
Optimizing Encoder Circuits of Entanglement-Assisted Quantum LDPC Codes via Beam Search
Aditya Sodhani, Pavan Kumar, Shayan Srinivasa Garani +1
In encoder circuits built on the stabilizer formalism, the dominant contribution to circuit complexity comes from the use of controlled (CNOT) gates, making CNOT-count reduction a…
An Iterated Hybrid Fast Parallel FIR Filter
Keshab K. Parhi
This paper revisits the design and optimization of parallel fast finite impulse response (FIR) filters using polyphase decomposition and iterated fast FIR algorithms (FFAs). Parall…
LayerPipe2: Multistage Pipelining and Weight Recompute via Improved Exponential Moving Average for Training Neural Networks
Nanda K. Unnikrishnan, Keshab K. Parhi
In our prior work, LayerPipe, we had introduced an approach to accelerate training of convolutional, fully connected, and spiking neural networks by overlapping forward and backwar…
The Equivalence of Fast Algorithms for Convolution, Parallel FIR Filters, Polynomial Modular Multiplication, and Pointwise Multiplication in DFT/NTT Domain
Keshab K. Parhi
Fast time-domain algorithms have been developed in signal processing applications to reduce the multiplication complexity. For example, fast convolution structures using Cook-Toom…
A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents
Abhijit Chatterjee, Niraj K. Jha, Jonathan D. Cohen +6
The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictate the prosperity and might of th…
Encoder Circuit Optimization for Non-Binary Quantum Error Correction Codes in Prime Dimensions: An Algorithmic Framework
Aditya Sodhani, Keshab K. Parhi
Quantum computers are a revolutionary class of computational platforms with applications in combinatorial and global optimization, machine learning, and other domains involving com…
A Survey of Attacks on Large Language Models
Wenrui Xu, Keshab K. Parhi
Large language models (LLMs) and LLM-based agents have been widely deployed in a wide range of applications in the real world, including healthcare diagnostics, financial analysis,…
An Optimized Nearest Neighbor Compliant Quantum Circuit for 5-qubit Code
Arijit Mondal, Keshab K. Parhi
The five-qubit quantum error correcting code encodes one logical qubit to five physical qubits, and protects the code from a single error. It was one of the first quantum codes to…
SpikePipe: Accelerated Training of Spiking Neural Networks via Inter-Layer Pipelining and Multiprocessor Scheduling
Sai Sanjeet, Bibhu Datta Sahoo, Keshab K. Parhi
Spiking Neural Networks (SNNs) have gained popularity due to their high energy efficiency. Prior works have proposed various methods for training SNNs, including backpropagation-ba…
Robust Clustering using Hyperdimensional Computing
Lulu Ge, Keshab K. Parhi
This paper addresses the clustering of data in the hyperdimensional computing (HDC) domain. In prior work, an HDC-based clustering framework, referred to as HDCluster, has been pro…
KyberMat: Efficient Accelerator for Matrix-Vector Polynomial Multiplication in CRYSTALS-Kyber Scheme via NTT and Polyphase Decomposition
Weihang Tan, Yingjie Lao, Keshab K. Parhi
CRYSTAL-Kyber (Kyber) is one of the post-quantum cryptography (PQC) key-encapsulation mechanism (KEM) schemes selected during the standardization process. This paper addresses opti…
Systematic Design and Optimization of Quantum Circuits for Stabilizer Codes
Arijit Mondal, Keshab K. Parhi
Quantum computing is an emerging technology that has the potential to achieve exponential speedups over their classical counterparts. To achieve quantum advantage, quantum principl…
Quantum Circuits for Stabilizer Error Correcting Codes: A Tutorial
Arijit Mondal, Keshab K. Parhi
Quantum computers have the potential to provide exponential speedups over their classical counterparts. Quantum principles are being applied to fields such as communications, infor…
A Low-Latency FFT-IFFT Cascade Architecture
Keshab K. Parhi
This paper addresses the design of a partly-parallel cascaded FFT-IFFT architecture that does not require any intermediate buffer. Folding can be used to design partly-parallel arc…
Long Polynomial Modular Multiplication using Low-Complexity Number Theoretic Transform
Sin-Wei Chiu, Keshab K. Parhi
This tutorial aims to establish connections between polynomial modular multiplication over a ring to circular convolution and discrete Fourier transform (DFT). The main goal is to…
Tensor Decomposition for Model Reduction in Neural Networks: A Review
Xingyi Liu, Keshab K. Parhi
Modern neural networks have revolutionized the fields of computer vision (CV) and Natural Language Processing (NLP). They are widely used for solving complex CV tasks and NLP tasks…
SCV-GNN: Sparse Compressed Vector-based Graph Neural Network Aggregation
Nanda K. Unnikrishnan, Joe Gould, Keshab K. Parhi
Graph neural networks (GNNs) have emerged as a powerful tool to process graph-based data in fields like communication networks, molecular interactions, chemistry, social networks,…
PaReNTT: Low-Latency Parallel Residue Number System and NTT-Based Long Polynomial Modular Multiplication for Homomorphic Encryption
Weihang Tan, Sin-Wei Chiu, Antian Wang +2
High-speed long polynomial multiplication is important for applications in homomorphic encryption (HE) and lattice-based cryptosystems. This paper addresses low-latency hardware ar…
Integral Sampler and Polynomial Multiplication Architecture for Lattice-based Cryptography
Antian Wang, Weihang Tan, Keshab K. Parhi +1
With the surge of the powerful quantum computer, lattice-based cryptography proliferated the latest cryptography hardware implementation due to its resistance against quantum compu…
Multi-Channel FFT Architectures Designed via Folding and Interleaving
Nanda K. Unnikrishnan, Keshab K. Parhi
Computing the FFT of a single channel is well understood in the literature. However, computing the FFT of multiple channels in a systematic manner has not been fully addressed. Thi…
High-Speed VLSI Architectures for Modular Polynomial Multiplication via Fast Filtering and Applications to Lattice-Based Cryptography
Weihang Tan, Antian Wang, Yingjie Lao +2
This paper presents a low-latency hardware accelerator for modular polynomial multiplication for lattice-based post-quantum cryptography and homomorphic encryption applications. Th…
LayerPipe: Accelerating Deep Neural Network Training by Intra-Layer and Inter-Layer Gradient Pipelining and Multiprocessor Scheduling
Nanda K. Unnikrishnan, Keshab K. Parhi
The time required for training the neural networks increases with size, complexity, and depth. Training model parameters by backpropagation inherently creates feedback loops. These…