Add to ORKGPresented at NiPS Summer School 2019, Perugia (Italy)This work presents results using transprecision techniques for reducing the precision of the computation of time series analysis. The developed benchmark allows to explore how the accuracy of the results is affected by this reduction in the precision of the data types. Custom hardware could benefit from this approach reducing energy consumption and improving performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
In the last five years there have been a large number of new time series classification algorithms p...
Energiency est une entreprise qui vend à des industriels une plate-forme pour leur permettre d’analy...
Time Series Classification (TSC) has received much attention in the past two decades and is still a ...
Time series analysis (TSA) comprises methods for extracting information in domains as diverse as med...
The explosion of the Internet-Of-Things and Big Data era has resulted in the continuous generation o...
Classical anomaly detection is principally concerned with point-based anomalies, those anomalies tha...
The Internet of Things (IoT) enables to connect multiple devices for providing a certain service, co...
Time Series Analysis (TSA) is a critical workload for consumer-facing devices. Accelerating TSA is v...
International audienceFull-precision Floating-Point Units (FPUs) can be a source of extensive hardwa...
Full-precision Floating-Point Units (FPUs) can be a source of extensive hardware overhead in general...
Time series analysis is an important research topic and a key step in monitoring and predicting even...
International audienceMore and more sensors are used in industrial systems (machines , plants, facto...
open3siIn recent years approximate computing has been extensively explored as a paradigm to design h...
In nearly all enterprises, time series-connected problems are a day-to-day issue which we should kno...
Time series classification (TSC) methods discover and exploit patterns in time series and other one-...
In the last five years there have been a large number of new time series classification algorithms p...
Energiency est une entreprise qui vend à des industriels une plate-forme pour leur permettre d’analy...
Time Series Classification (TSC) has received much attention in the past two decades and is still a ...
Time series analysis (TSA) comprises methods for extracting information in domains as diverse as med...
The explosion of the Internet-Of-Things and Big Data era has resulted in the continuous generation o...
Classical anomaly detection is principally concerned with point-based anomalies, those anomalies tha...
The Internet of Things (IoT) enables to connect multiple devices for providing a certain service, co...
Time Series Analysis (TSA) is a critical workload for consumer-facing devices. Accelerating TSA is v...
International audienceFull-precision Floating-Point Units (FPUs) can be a source of extensive hardwa...
Full-precision Floating-Point Units (FPUs) can be a source of extensive hardware overhead in general...
Time series analysis is an important research topic and a key step in monitoring and predicting even...
International audienceMore and more sensors are used in industrial systems (machines , plants, facto...
open3siIn recent years approximate computing has been extensively explored as a paradigm to design h...
In nearly all enterprises, time series-connected problems are a day-to-day issue which we should kno...
Time series classification (TSC) methods discover and exploit patterns in time series and other one-...
In the last five years there have been a large number of new time series classification algorithms p...
Energiency est une entreprise qui vend à des industriels une plate-forme pour leur permettre d’analy...
Time Series Classification (TSC) has received much attention in the past two decades and is still a ...