Electrical-level attacks on CPUs, FPGAs, and GPUs: Survey and implications in the heterogeneous era
Given the need for efficient high-performance computing, computer architectures combining
central processing units (CPUs), graphics processing units (GPUs), and field-programmable …
central processing units (CPUs), graphics processing units (GPUs), and field-programmable …
Characterization and prediction of deep learning workloads in large-scale gpu datacenters
Modern GPU datacenters are critical for delivering Deep Learning (DL) models and services
in both the research community and industry. When operating a datacenter, optimization of …
in both the research community and industry. When operating a datacenter, optimization of …
Energy‐aware high‐performance computing: survey of state‐of‐the‐art tools, techniques, and environments
The paper presents state of the art of energy‐aware high‐performance computing (HPC), in
particular identification and classification of approaches by system and device types …
particular identification and classification of approaches by system and device types …
Evaluating the energy efficiency of deep convolutional neural networks on CPUs and GPUs
In recent years convolutional neural networks (CNNs) have been successfully applied to
various applications that are appropriate for deep learning, from image and video …
various applications that are appropriate for deep learning, from image and video …
The impact of GPU DVFS on the energy and performance of deep learning: An empirical study
Over the past years, great progress has been made in improving the computing power of
general-purpose graphics processing units (GPGPUs), which facilitates the prosperity of …
general-purpose graphics processing units (GPGPUs), which facilitates the prosperity of …
iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud
GPUs are essential to accelerating the latency-sensitive deep neural network (DNN)
inference workloads in cloud datacenters. To fully utilize GPU resources, spatial sharing of …
inference workloads in cloud datacenters. To fully utilize GPU resources, spatial sharing of …
[HTML][HTML] A survey and measurement study of GPU DVFS on energy conservation
Energy efficiency has become one of the top design criteria for current computing systems.
The dynamic voltage and frequency scaling (DVFS) has been widely adopted by laptop …
The dynamic voltage and frequency scaling (DVFS) has been widely adopted by laptop …
Apparatus and method for optimizing quantifiable behavior in configurable devices and systems
H Hoffmann, J Lafferty, N Mishra - US Patent 11,009,836, 2021 - Google Patents
An apparatus and method are provided to perform constrained optimization of a constrained
property of an apparatus, which is complex due to having several components, and these …
property of an apparatus, which is complex due to having several components, and these …
{EnvPipe}: Performance-preserving {DNN} training framework for saving energy
Energy saving is a crucial mission for data center providers. Among many services, DNN
training and inference are significant contributors to energy consumption. This work focuses …
training and inference are significant contributors to energy consumption. This work focuses …
Not all gpus are created equal: characterizing variability in large-scale, accelerator-rich systems
Scientists are increasingly exploring and utilizing the massive parallelism of general-
purpose accelerators such as GPUs for scientific breakthroughs. As a result, datacenters …
purpose accelerators such as GPUs for scientific breakthroughs. As a result, datacenters …