Learn More
Parallel computation, a greater advancement in computational hardware as well as new achievement in current scientific computing such as image processing involves huge exhaustive computation and data processing leading towards parallel architectures. Parallel hardware organization basically a suitable interconnection among computational hardware, where(More)
Workload distribution among processors is one sided task. Whereas consistent management of processor availability to bulk job arrival is an aspect of resource management. Parallel systems where high probability of infinite job arrivals with varying processor demand requires a lot of adjustment efforts to map processors space over job space. Each job has(More)
Hadoop is one of the most popular technologies used in the big data landscape for evaluating the data through Hadoop Distributed File System and Map-Reduce. Problems which are larger in size are becoming tough to handle by a single system these days because the execution time for such problems will be very high in such platform. Instead of processing the(More)
Virtualization helps a lot in handling critical applications in a highly availability manner, stream lining in applications deployment, application migrations etc. It is because of the virtualization that users are able to reduce the extra requirements of hardware, power consumption, trimming the space requirements, air conditioning requirements etc. Server(More)
There are number of problems that are so complex/large that it becomes impractical or even in some cases impossible to solve these problems on a single machine. As compared to the serial computation, parallel computation is much result oriented for understanding, simulating of number of complex and real world physical process. The cache oblivious(CO) model(More)
  • 1