A Trade-Off between Computing Power and Energy Consumption of On-Board Data Processing in GPU Accelerated In-Orbit Space Systems

Tsog, Nandinbaatar; Mubeen, Saad; Sjödin, Mikael; Bruhn, Fredrik

doi:10.2322/tastj.19.700

Cited by 1 publication

(1 citation statement)

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“…Notice that under certain circumstances, a trade-off exists of the accuracy of the solution obtained using parallelism versus the solution using sequential paradigm. 48 In our parallel implementation, there is no trade-off using parallelism versus the sequential algorithm since we only accelerate the searching of the parameters of Equation 6. The same result is obtained using the parallel and the sequential implementations.…”

Section: Parallel Algorithm Pardwdmmentioning

confidence: 99%

Implementation and evaluation of two parallel computational models for the simulation of a long‐haul DWDM system limited by FWM

Sánchez‐Lara,

López‐Martínez,

Trejo‐Sánchez

et al. 2023

Concurrency and Computation

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Four‐Wave Mixing (FWM) is one of the non‐linear phenomena affecting long‐reach communication systems and high bandwidth. Research communities use simulation tools for parameter optimization. Unfortunately, such a simulation is time‐consuming and requires more time as the number of channels increases. This paper proposes two fast implementations of Dense Wavelength Division Multiplexing (DWDM) system, limited by FWM and the intrinsic Amplified Spontaneous Emission (ASE) noise of optical amplifiers employed in each segment. Additionally, this work compares the efficiency and speed improvement of the proposed parallelization model versus an earlier sequential model. We present the computational complexity analysis of sequential and parallel models. The paper considers two different parallel implementations: a multicore processor using Open MultiProcessing (OpenMP) and Compute Unified Device Architecture (CUDA), which is based on the use of a Graphics Processing Unit (GPU). Results show that parallelism using CUDA improves by up to 70 times the simulation performance compared to the sequential model. Parallelism with CUDA is up to 15 times compared to OpenMP using 12 logical processors. It is possible to simulate an increased number of channels within our parallel execution, which was impractical in the sequential simulation.

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Section: Parallel Algorithm Pardwdmmentioning

confidence: 99%