Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Cao, Jiashen"'
Query optimization in relational database management systems (DBMSs) is critical for fast query processing. The query optimizer relies on precise selectivity and cost estimates to effectively optimize queries prior to execution. While this strategy i
Externí odkaz:
http://arxiv.org/abs/2403.14902
GPUs offer massive compute parallelism and high-bandwidth memory accesses. GPU database systems seek to exploit those capabilities to accelerate data analytics. Although modern GPUs have more resources (e.g., higher DRAM bandwidth) than ever before,
Externí odkaz:
http://arxiv.org/abs/2302.00734
The increasing interest in serverless computation and ubiquitous wireless networks has led to numerous connected devices in our surroundings. Among such devices, IoT devices have access to an abundance of raw data, but their inadequate resources in c
Externí odkaz:
http://arxiv.org/abs/2104.04447
To efficiently process visual data at scale, researchers have proposed two techniques for lowering the computational overhead associated with the underlying deep learning models. The first approach consists of leveraging a specialized, lightweight mo
Externí odkaz:
http://arxiv.org/abs/2102.08481
Satisfying the high computation demand of modern deep learning architectures is challenging for achieving low inference latency. The current approaches in decreasing latency only increase parallelism within a layer. This is because architectures typi
Externí odkaz:
http://arxiv.org/abs/2011.07092
Autor:
Hadidi, Ramyad, Asgari, Bahar, Cao, Jiashen, Bae, Younmin, Shim, Da Eun, Kim, Hyojong, Lim, Sung-Kyu, Ryoo, Michael S., Kim, Hyesoon
Deep neural networks (DNNs) have inspired new studies in myriad edge applications with robots, autonomous agents, and Internet-of-things (IoT) devices. However, performing inference of DNNs in the edge is still a severe challenge, mainly because of t
Externí odkaz:
http://arxiv.org/abs/2003.06464
With recent advancements in deep neural networks (DNNs), we are able to solve traditionally challenging problems. Since DNNs are compute intensive, consumers, to deploy a service, need to rely on expensive and scarce compute resources in the cloud. T
Externí odkaz:
http://arxiv.org/abs/1901.02537
The prevalence of Internet of things (IoT) devices and abundance of sensor data has created an increase in real-time data processing such as recognition of speech, image, and video. While currently such processes are offloaded to the computationally
Externí odkaz:
http://arxiv.org/abs/1802.02138
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.