Heterogeneous computer systems are becoming mainstream due to their disparate
processing and performance capabilities. These systems consist of different types of …

Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL
has resulted in greatly reducing the execution time of data-parallel applications by taking …

Load balancing plays a critical role in ensuring system stability and optimal performance,
and as such, it has been a subject of extensive research across diverse computing domains …

The essential component of the Big Data system is the processing frameworks and engines
responsible for crunching the data. To cope with the growing computing demands of real …

Graphical Processing Units (GPUs) are increasingly being incorporated to High-
performance computing (HPC) systems alongside Central Processing Units (CPUs). As a …

Big data, cloud computing, and artificial intelligence technologies supported by
heterogeneous systems are constantly changing our life and cognition of the world. At the …

Background A scheduling algorithm tries to schedule multiple computational tasks on a
cluster of multiple computing nodes to maximize throughput with optimal utilization of …

TensorFlow, a popular machine learning (ML) platform, allows users to transparently exploit
both GPUs and CPUs to run their applications. Since GPUs are optimized for compute …

In the past decade, heterogeneous multicore architectures with support for Single Instruction
Multiple Thread (SIMT) style computing have become the standard platform of choice for …

In this paper, we propose an energy saving strategy for heterogeneous clusters. A load
balancer is then proposed by using code features and a resource-aware processor selection …