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High Performance Computing

High Performance Computing studies on obtaining the best utilization of the hardware at hand for large and time-critical computing tasks. The continuous architectural evolution of the computer clusters, network infrastructures, multi- and many-core processors and accelerators necessitates heterogeneous computation and novel parallelization techniques and optimized, topology-aware implementations of data analytics kernels to minimize the energy usage and computing costs and to obtain the best performance.

Faculty members: Kamer Kaya

Funded Projetcs:

  • 2015-2017, TÜBİTAK 2232 Project (No: 115C018): "High Performance Computing on Big and Streaming Data". K. Kaya.
The performance chart of a novel, parallel algorithm
designed to find the most important and central nodes in a social
network on a single Xeon Phi accelerator. a GTEPS: the number of
social-network friendships per second (in billions The performance chart of a novel, parallel algorithm designed to find the most important and central nodes in a social network on a single Xeon Phi accelerator. a GTEPS: the number of social-network friendships per second (in billions).