High performance computing (HPC) clouds are becoming an alternative to on-premise
clusters for executing scientific applications and business analytics services. Most research …

Nowadays, high-performance computing (HPC) clusters are increasingly popular. Large
volumes of job logs recording many years of operation traces have been accumulated. In the …

Scalability is a key feature for big data analysis and machine learning frameworks and for
applications that need to analyze very large and real-time data available from data …

Scaling a parallel program to modern supercomputers is challenging due to inter-process
communication, Amdahl's law, and resource contention. Performance analysis tools for …

Particle filtering has been a very popular method to solve nonlinear/non-Gaussian state
estimation problems for more than twenty years. Particle filters (PFs) have found lots of …

Cloud providers are auctioning their excess capacity using dynamically priced virtual
instances. These spot instances provide significant savings compared to on-demand or fixed …

With the continual increase in the high performance computing (HPC) market share, the
need for a cheaper and widely available system rather than the expensive typical HPC …

While cloud computing is widely adopted in many application domains, it is not yet the case
for the high performance computing (HPC) domain. HPC traditionally runs on …

Scaling a parallel program to modern supercomputers is challenging due to inter-process
communication, Amdahl's law, and resource contention. Performance analysis tools for …

Graduates with high performance computing (HPC) skills are more in demand than ever
before, most recently fueled by the rise of artificial intelligence and big data technologies …