CPU-GPU cooperative QoS optimization of personalized digital healthcare using machine learning and swarm intelligence
In recent decades, the rapid advances in information technology have promoted a
widespread deployment of medical cyber-physical systems (MCPS), especially in the area of …
widespread deployment of medical cyber-physical systems (MCPS), especially in the area of …
TMDS: Temperature-aware makespan minimizing DAG scheduler for heterogeneous distributed systems
To meet application-specific performance demands, recent embedded platforms often
involve the use of intricate micro-architectural designs and very small feature sizes leading …
involve the use of intricate micro-architectural designs and very small feature sizes leading …
Regulating CPU temperature with thermal-aware scheduling using a reduced order learning thermal model
Modern real-time systems utilize considerable amounts of power while executing
computation-intensive tasks. The execution of these tasks leads to significant power …
computation-intensive tasks. The execution of these tasks leads to significant power …
Toward Energy-efficient STT-MRAM-based Near Memory Computing Architecture for Embedded Systems
Convolutional Neural Networks (CNNs) have significantly impacted embedded system
applications across various domains. However, this exacerbates the real-time processing …
applications across various domains. However, this exacerbates the real-time processing …
An effective physics simulation methodology based on a data-driven learning algorithm
A methodology of multi-dimensional physics simulations is investigated based on a data-
driven learning algorithm derived from proper orthogonal decomposition (POD). The …
driven learning algorithm derived from proper orthogonal decomposition (POD). The …
Harnessing Machine Learning in Dynamic Thermal Management in Embedded CPU-GPU Platforms
With increasing transistor density, modern heterogeneous embedded processors often
exhibit high temperature gradients due to complex application scheduling scenarios which …
exhibit high temperature gradients due to complex application scheduling scenarios which …
An Evaluation Framework for Dynamic Thermal Management Strategies in 3D MultiProcessor System-on-Chip Co-Design
Dynamic thermal management (DTM) has been widely adopted to improve the energy
efficiency, reliability, and performance of modern Multi-Processor SoCs (MPSoCs) …
efficiency, reliability, and performance of modern Multi-Processor SoCs (MPSoCs) …
Inferencing on Edge Devices: A Time-and Space-aware Co-scheduling Approach
Neural Network (NN)-based real-time inferencing tasks are often co-scheduled on GPGPU-
style edge platforms. Existing works advocate using different NN parameters for the same …
style edge platforms. Existing works advocate using different NN parameters for the same …
Hot Under the Hood: An Analysis of Ambient Temperature Impact on Heterogeneous Edge Platforms
Applications deployed at the edge are often subject to critical Quality of Service (QoS)
objectives, such as meeting deadlines while optimizing for energy consumption. To design …
objectives, such as meeting deadlines while optimizing for energy consumption. To design …
Future aware dynamic thermal management in cpu-gpu embedded platforms
Modern data intensive Cyber-physical Systems ubiquitously employ heterogeneous
multiprocessor systems-on chips (MPSoCs) for real-time sensing, computation, and …
multiprocessor systems-on chips (MPSoCs) for real-time sensing, computation, and …