Zobrazeno 1 - 10
of 359
pro vyhledávání: '"Chakrabarti, Chaitali"'
Autor:
Li, Jingtao, Rakin, Adnan Siraj, Chen, Xing, Yang, Li, He, Zhezhi, Fan, Deliang, Chakrabarti, Chaitali
Federated Learning (FL) is a popular collaborative learning scheme involving multiple clients and a server. FL focuses on protecting clients' data but turns out to be highly vulnerable to Intellectual Property (IP) threats. Since FL periodically coll
Externí odkaz:
http://arxiv.org/abs/2303.08581
Autor:
Yang, Yichen, Li, Jingtao, Talati, Nishil, Pal, Subhankar, Feng, Siying, Chakrabarti, Chaitali, Mudge, Trevor, Dreslinski, Ronald
The irregular nature of memory accesses of graph workloads makes their performance poor on modern computing platforms. On manycore reconfigurable architectures (MRAs), in particular, even state-of-the-art graph prefetchers do not work well (only 3% s
Externí odkaz:
http://arxiv.org/abs/2301.12312
Autor:
Chang, Liangliang, Mack, Joshua, Willis, Benjamin, Chen, Xing, Brunhaver, John, Akoglu, Ali, Chakrabarti, Chaitali
In this study, we introduce a methodology for automatically transforming user applications in the radar and communication domain written in C/C++ based on dynamic profiling to a parallel representation targeted for a heterogeneous SoC. We present our
Externí odkaz:
http://arxiv.org/abs/2211.14547
Line-of-sight link blockages represent a key challenge for the reliability and latency of millimeter wave (mmWave) and terahertz (THz) communication networks. To address this challenge, this paper leverages mmWave and LiDAR sensory data to provide aw
Externí odkaz:
http://arxiv.org/abs/2211.09535
Sampling is an essential part of raw point cloud data processing such as in the popular PointNet++ scheme. Farthest Point Sampling (FPS), which iteratively samples the farthest point and performs distance updating, is one of the most popular sampling
Externí odkaz:
http://arxiv.org/abs/2208.08795
This work aims to tackle Model Inversion (MI) attack on Split Federated Learning (SFL). SFL is a recent distributed training scheme where multiple clients send intermediate activations (i.e., feature map), instead of raw data, to a central server. Wh
Externí odkaz:
http://arxiv.org/abs/2205.04007
Line-of-sight link blockages represent a key challenge for the reliability and latency of millimeter wave (mmWave) and terahertz (THz) communication networks. This paper proposes to leverage LiDAR sensory data to provide awareness about the communica
Externí odkaz:
http://arxiv.org/abs/2111.09581
Overcoming the link blockage challenges is essential for enhancing the reliability and latency of millimeter wave (mmWave) and sub-terahertz (sub-THz) communication networks. Previous approaches relied mainly on either (i) multiple-connectivity, whic
Externí odkaz:
http://arxiv.org/abs/2111.08242
Autor:
Krishnan, Gokul, Mandal, Sumit K., Pannala, Manvitha, Chakrabarti, Chaitali, Seo, Jae-sun, Ogras, Umit Y., Cao, Yu
In-memory computing (IMC) on a monolithic chip for deep learning faces dramatic challenges on area, yield, and on-chip interconnection cost due to the ever-increasing model sizes. 2.5D integration or chiplet-based architectures interconnect multiple
Externí odkaz:
http://arxiv.org/abs/2108.08903
Autor:
Kim, Sung, Fayazi, Morteza, Daftardar, Alhad, Chen, Kuan-Yu, Tan, Jielun, Pal, Subhankar, Ajayi, Tutu, Xiong, Yan, Mudge, Trevor, Chakrabarti, Chaitali, Blaauw, David, Dreslinski, Ronald, Kim, Hun-Seok
We present Versa, an energy-efficient processor with 36 systolic ARM Cortex-M4F cores and a runtime-reconfigurable memory hierarchy. Versa exploits algorithm-specific characteristics in order to optimize bandwidth, access latency, and data reuse. Mea
Externí odkaz:
http://arxiv.org/abs/2109.03024