Technological advancement has enabled us to store and process huge amount of data in
relatively short spans of time. The nature of data is rapidly changing, particularly its …

Sparse Matrix-vector Multiplication (SpMV) is an important computation kernel widely used
in HPC and data centers. The irregularity of SpMV is a well-known challenge that limits …

Data generation is a key issue in big data benchmarking that aims to generate application-
specific data sets to meet the 4 V requirements of big data. Specifically, big data generators …

Combining the Internet-of-Things (IoT) technology with cloud computing is a significant
alternative for powering the utilization of computing resources in a connected environment …

Due to increasing amounts of data and compute resources, the deep learning achieves
many successes in various domains. Recently, researchers and engineers make effort to …

Modern micro-service and container-based cloud-native applications have leveraged multi-
tenancy as a first class system design concern. The increasing number of co-located …

Analytics based on big data computing can benefit today's banking and financial
organizations on many aspects, and provide much valuable information for organizations to …

When considering popular On-line Social Networks (OSN) containing heterogeneous
multimedia data sources, the complexity of the underlying processing systems becomes …

Connected and autonomous vehicles (CAVs) have recently attracted a significant amount of
attention both from researchers and industry. Numerous studies targeting algorithms …

In high performance computing systems, object deserialization can become a surprisingly
important bottleneck---in our test, a set of general-purpose, highly parallelized applications …