15 citations · 28 across the 6 of their papers we have counts for
6 papers
Data-aware Dynamic Execution of Irregular Workloads on Heterogeneous Systems
Zhenyu Bai, Dan Wu, Pranav Dangi +3
Current approaches to scheduling workloads on heterogeneous systems with specialized accelerators often rely on manual partitioning, offloading tasks with specific compute patterns…
Multiply-and-Fire (MNF): An Event-driven Sparse Neural Network Accelerator
Miao Yu, Tingting Xiang, Venkata Pavan Kumar Miriyala +1
Machine learning, particularly deep neural network inference, has become a vital workload for many computing systems, from data centers and HPC systems to edge-based computing. As…
Ultra-low power on-chip learning of speech commands with phase-change memories
Venkata Pavan Kumar Miriyala, Masatoshi Ishii
Embedding artificial intelligence at the edge (edge-AI) is an elegant solution to tackle the power and latency issues in the rapidly expanding Internet of Things. As edge devices t…
Electrical generation and detection of terahertz signal based on spin-wave emission from ferrimagnets
Zhifeng Zhu, Kaiming Cai, Jiefang Deng +4
Terahertz (THz) signals, mainly generated by photonic or electronic approaches, are being sought for various applications, whereas the development of magnetic source might be a nec…
SIMBA: A Skyrmionic In-Memory Binary Neural Network Accelerator
Venkata Pavan Kumar Miriyala, Kale Rahul Vishwanath, Xuanyao Fong
Magnetic skyrmions are emerging as potential candidates for next generation non-volatile memories. In this paper, we propose an in-memory binary neural network (BNN) accelerator ba…
Spin-wave mediated interactions for Majority Computation using Skyrmions and Spin-torque Nano-oscillators
Venkata Pavan Kumar Miriyala, Zhifeng Zhu, Gengchiau Liang +1
Recent progress in all-electrical nucleation, detection and manipulation of magnetic skyrmions has unlocked the tremendous potential of skyrmion-based spintronic devices. Here, we…