Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Jones, Alex K."'
Autor:
McKinney, Evan, Falstin, Girgis, Yusuf, Israa G., Agarwal, Gaurav, Hatridge, Michael, Jones, Alex K.
This paper addresses frequency crowding constraints in modular quantum architecture design, focusing on the SNAIL-based quantum modules. Two key objectives are explored. First, we present physics-informed design constraints by describing a physical m
Externí odkaz:
http://arxiv.org/abs/2409.18262
Autor:
de Lima, João Paulo Cardoso, Morris III, Benjamin Franklin, Khan, Asif Ali, Castrillon, Jeronimo, Jones, Alex K.
Big data processing has exposed the limits of compute-centric hardware acceleration due to the memory-to-processor bandwidth bottleneck. Consequently, there has been a shift towards memory-centric architectures, leveraging substantial compute paralle
Externí odkaz:
http://arxiv.org/abs/2409.10136
Autor:
Brazzle, Preston, Morris III, Benjamin F., McKinney, Evan, Zhou, Peipei, Hu, Jingtong, Khan, Asif Ali, Jones, Alex K.
Computing-in-memory (CIM) promises to alleviate the Von Neumann bottleneck and accelerate data-intensive applications. Depending on the underlying technology and configuration, CIM enables implementing compute primitives in place, such as multiplicat
Externí odkaz:
http://arxiv.org/abs/2407.21661
The rising demand for on-demand, high-performance computing has led to the growth of data centers, which in turn presents both challenges and opportunities for addressing their environmental impact. Traditionally, sustainability efforts in data cente
Externí odkaz:
http://arxiv.org/abs/2403.04976
Autor:
Li, Sheng, Yuan, Geng, Wu, Yawen, Dai, Yue, Wang, Tianyu, Wu, Chao, Jones, Alex K., Hu, Jingtong, Wang, Yanzhi, Tang, Xulong
Many emerging applications, such as robot-assisted eldercare and object recognition, generally employ deep learning neural networks (DNNs) and require the deployment of DNN models on edge devices. These applications naturally require i) handling stre
Externí odkaz:
http://arxiv.org/abs/2401.16694
Autor:
Zhuang, Jinming, Yang, Zhuoping, Ji, Shixin, Huang, Heng, Jones, Alex K., Hu, Jingtong, Shi, Yiyu, Zhou, Peipei
Publikováno v:
2024 ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA '24)
With the increase in the computation intensity of the chip, the mismatch between computation layer shapes and the available computation resource significantly limits the utilization of the chip. Driven by this observation, prior works discuss spatial
Externí odkaz:
http://arxiv.org/abs/2401.10417
Autor:
Ji, Shixin, Yang, Zhuoping, Chen, Xingzhen, Cahoon, Stephen, Hu, Jingtong, Shi, Yiyu, Jones, Alex K., Zhou, Peipei
Embodied carbon has been widely reported as a significant component in the full system lifecycle of various computing systems' green house gas emissions. Many efforts have been undertaken to quantify the elements that comprise this embodied carbon, f
Externí odkaz:
http://arxiv.org/abs/2401.06270
Autor:
Zhou, Peipei, Zhuang, Jinming, Cahoon, Stephen, Tang, Yue, Yang, Zhuoping, Chen, Xingzhen, Shi, Yiyu, Hu, Jingtong, Jones, Alex K.
There is a growing call for greater amounts of increasingly agile computational power for edge and cloud infrastructure to serve the computationally complex needs of ubiquitous computing devices. Thus, an important challenge is addressing the holisti
Externí odkaz:
http://arxiv.org/abs/2312.02991
Arbitrary-precision integer multiplication is the core kernel of many applications in simulation, cryptography, etc. Existing acceleration of arbitrary-precision integer multiplication includes CPUs, GPUs, FPGAs, and ASICs. Among these accelerators,
Externí odkaz:
http://arxiv.org/abs/2309.12275
Building efficient large-scale quantum computers is a significant challenge due to limited qubit connectivities and noisy hardware operations. Transpilation is critical to ensure that quantum gates are on physically linked qubits, while minimizing $\
Externí odkaz:
http://arxiv.org/abs/2308.03874