The papers will help you to understand the concept of Exascale Computing, opportunities and challenges, and the needs of exascale computers. This topic should be concentrated on by Computer Science engineers and researchers to overcome the issues of performance and programming in the current computing scale. There are many scientific disciplines from biology to nuclear engineering, computing at the exascale computing promises dramatic advances in our capabilities to model and simulate complex phenomena, at levels of fidelity that have the potential to dramatically change both our understanding and our ability to comprehend.
Moving to an exascale will mean a complete change in computing architecture.– basically, vastly increasing the levels of parallelism to the point of millions of processors working in tandem – which will force radical changes in how hardware is designed (at minimum, driven by economic limitations on power consumption), in how we go about solving problems (e.g., the application codes), and in how we marry application codes to the underlying hardware (e.g., the compilers, I/O, middleware, and related software tools). Understanding the advantages of exascale computing, and evaluating the risks involved by going down this path, requires both an evaluation of past experiences in moving from the megaflop era to the present petaflop era, as well as an assessment of the readiness of advanced applications to take transformative advantage of exascale computing.
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