M. Suhail Rehman

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MapReduce is by far one of the most successful realizations of large-scale data-intensive cloud computing platforms. MapReduce automatically parallelizes computation by running multiple map and/or reduce tasks over distributed data across multiple machines. Hadoop is an open source implementation of MapReduce. When Hadoop schedules reduce tasks, it neither(More)
Cloud computing offers a paradigm shift in management of computing resources for large-scale applications. Using the Infrastructure-as-a-service (IaaS) cloud computing model, users today can request dynamically provisioned, virtualized resources such as CPU, memory, disk, and network access in the form of virtualized resources. The client typically requests(More)
The significant growth in computational power of modern Graphics Processing Units (GPUs) coupled with the advent of general purpose programming environments like NVIDIA's CUDA, has seen GPUs emerging as a very popular parallel computing platform. Till recently, there has not been a performance model for GPGPUs. The absence of such a model makes it difficult(More)
Large-scale distributed processing frameworks such as Hadoop are currently enjoying wide popularity for big data computation. Performance Analysis and monitoring under these frameworks are inherently difficult especially in a virtualized environment. Existing distributed monitoring tools can only report virtual resource usage. Such reported information(More)
We have designed, developed and administered a course on cloud computing that was taught to over 700 students at our institution over two years. The goal of this project-based course is to provide students with foundational systems concepts as well as experience in developing the required skills to design and deploy viable, robust and elastic web-services(More)
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