Abstract—We present a scalable spatial decomposition coloring approach to implement molecular dynamics simulations with embedded atom method (EAM) on multi-core architectures. It effectively solves parallelization of reduction operations on irregular arrays in molecular dynamics simulations

Multi-core platforms have proven themselves able to accelerate numerous HPC applications. But programming dataintensive applications on such platforms is a hard, and not yet solved, problem. Not only do modern processors favor compute-intensive code, they also have diverse architectures

As multi-core processors with tens or hundreds of cores begin to proliferate, system optimization issues once faced only by the high-performance computing (HPC) community will become important to all programmers. However, unlike with HPC, the focus of the multi-core programmer

of the obtained performance. It requires understanding the problem being solved. In this work we evaluate the performance achieved by a suffix array over a 32-core platform.

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Cyber-physical systems (CPS) involve embedded computing devices that interact with physical processes. CPS require a software and hardware architecture that not only delivers good performance but also good predictability. In particular, CPS software must maintain good responsiveness while using a bounded amount of memory, processor, and power resources. Most importantly, CPS software must be real-time; i.e. the

requirements, performing IPv6 lookup at wire-speed is challenging. In this work, we propose a high-performance IPv6 lookup engine solution for multi-core platforms that deliver state-of-the-art line card throughput rates. In order to exploit the parallelism offered on modern multi-core platforms, we propose a

Abstract—We present Huckleberry, a tool for automatically generating parallel implementations for multi-core platforms from sequential recursive divide-and-conquer programs. The recursive programming model is a good match for parallel systems because it highlights the temporal and spatial locality

for the inversion of a symmetric positive definite matrix on multi-core platforms are studied and evaluated, the traditional approach based on the Cholesky factorization and the Gauss-Jordan elimination algorithm. Implementations of both methods have been developed and tested. Numerical experiments show

Multi-core platforms have proven themselves able to accel-erate numerous HPC applications. But programming data-intensive applications on such platforms is a hard, and not yet solved, problem. Not only do modern processors favor compute-intensive code, they also have diverse architectures