Abstract
We present a parallel implementation of an algorithm for calculating the two-point angular correlation function as applied in the field of computational cosmology. The algorithm has been specifically developed for a reconfigurable computer. Our implementation utilizes a microprocessor and two reconfigurable processors on a dual-MAP SRC-6 system. The two reconfigurable processors are used as two application-specific co-processors. Two independent computational kernels are simultaneously executed on the reconfigurable processors while data pre-fetching from disk and initial data pre-processing are executed on the microprocessor. The overall end-to-end algorithm execution speedup achieved by this implementation is over 90× as compared to a sequential implementation of the algorithm executed on a single 2.8 GHz Intel Xeon microprocessor.
Highlights
Correlation analyses are a common tool from the field of spatial statistics, and thereby impact a wide range of scientific disciplines
Reconfigurable computing [7] based on the use of Field-Programmable Gate Array (FPGA) technology has evolved to the point where it can accelerate computationally intensive floating-point scientific codes beyond what is possible on conventional, microprocessor-based systems [21]
We present a parallel implementation of a two-point angular correlation function (TPACF) algorithm on an SRC-6 reconfigurable computer in which the workload is distributed between a microprocessor and two reconfigurable processors, each consisting of two FPGAs
Summary
Correlation analyses are a common tool from the field of spatial statistics, and thereby impact a wide range of scientific disciplines. A common coordinate choice is the angular separations, θ, on the celestial sphere, which can be used to measure the angular two-point correlation function, which we will denote here as ω(θ). Reconfigurable computing [7] based on the use of Field-Programmable Gate Array (FPGA) technology has evolved to the point where it can accelerate computationally intensive floating-point scientific codes beyond what is possible on conventional, microprocessor-based systems [21]. V.V. Kindratenko et al / Implementation of the two-point angular correlation function on an HPRC sor used as an application-specific co-processor to accelerate the computationally-intensive portion of the code.
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