FFT Implementation on a Streaming Architecture

Lobeiras, Jacobo; Amor, Margarita; Doallo, Ramón

doi:10.1109/pdp.2011.31

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…Romein (2013) shows that FFTs on GPUs are heavily IO bound, and achieve around 20% of the peak performance, comparable with CPUs. Research by Lobeiras et al (2011) and nVidia’s own CUFFT library confirm this.…”

Section: The Ska1 On Today’s Technologymentioning

confidence: 71%

Challenges in exascale radio astronomy: Can the SKA ride the technology wave?

Vermij

Fiorin

Jongerius

et al. 2014

The International Journal of High Performance Computing Applica

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The Square Kilometre Array (SKA) will be the most sensitive radio telescope in the world. This unprecedented sensitivity will be achieved by combining and analyzing signals from 262,144 antennas and 350 dishes at a raw datarate of petabits per second. The processing pipeline to create useful astronomical data will require hundreds of peta-operations per second, at a very limited power budget. We analyze the compute, memory and bandwidth requirements for the key algorithms used in the SKA. By studying their implementation on existing platforms, we show that most algorithms have properties that map inefficiently on current hardware, such as a low compute–bandwidth ratio and complex arithmetic. In addition, we estimate the power breakdown on CPUs and GPUs, analyze the cache behavior on CPUs, and discuss possible improvements. This work is complemented with an analysis of supercomputer trends, which demonstrates that current efforts to use commercial off-the-shelf accelerators results in a two to three times smaller improvement in compute capabilities and power efficiency than custom built machines. We conclude that waiting for new technology to arrive will not give us the instruments currently planned in 2018: one or two orders of magnitude better power efficiency and compute capabilities are required. Novel hardware and system architectures, to match the needs and features of this unique project, must be developed.

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Section: The Ska1 On Today’s Technologymentioning

confidence: 71%

Challenges in exascale radio astronomy: Can the SKA ride the technology wave?

Vermij

Fiorin

Jongerius

et al. 2014

The International Journal of High Performance Computing Applica

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“…the IFFT Gerstner wave. IFFT has a large degree of parallelism in each stage of the computation [16] and its implementation is efficiently speeded up by GPU [17]. Tessendorf [18] is the pioneer of applying the IFFT Gerstner wave model in graphics.…”

Section: Introductionmentioning

confidence: 99%

Amplitude Malformation in the IFFT Ocean Wave Rendering under the Influence of the Fourier Coefficient

Chen¹,

Ye²,

Yong³

2014

ELS

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Although Tessendorf’s IFFT Gerstner wave model hasbeen widely used, the value of A, a constant of the Fouriercoefficient, is not given. A will strongly influence the shape of therendered ocean wave and even cause amplitude malformation.We study the algorithm of the IFFT Gerstner wave, and give themethod of A calculating. The method of the paper can guaranteethere is no amplitude malformation in rendered ocean waves. Theexpression of the IFFT Gerstner wave with the amplitude of thecosine wave is derived again. The definite integral of the wavenumber spectrum is discretized. Further, another expression ofthe IFFT Gerstner wave is gotten. The Fourier coefficient of theexpression contains the wave number spectrum and the area ofthe discrete integral domain. The method makes the shape of thegenerated wave stable. Comparing Tessdendorf’s method with themethod of the paper, we find that the expression of A shouldcontain the area of the discrete integral domain and the spectralconstant of the wave number spectrum. If A contains only thespectral constant, the amplitude malformation may occur. Byreading some well known open source codes, we find that the codeauthors adopted some factitious methods to suppress themalformed amplitude Obviously, the code authors have alreadynoticed the phenomenon of the malformation, but not probed thecause. The rendering results of the codes are close to that of themethod of the paper. Furthermore, the wave potential iscomputed using the Gerstner wave model directly, the author findit is quite close to that of the paper. The experimental results andcomparisons show that the method of the paper correctlycomputes the wave potential and effectively solves the problem ofamplitude malformation.

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“…Dentro de las más importantes se encuentran: solución de ecuaciones simultáneas [51], diferentes tipos de transformadas [52], [53], [54], soluciones de la ecuación de onda 2D y 3D [12], [55], comunicaciones [56], simulaciones de dinámica molecular [57], entre otras.…”

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Reducción de los tiempos de cómputo de la Migración Sísmica usando FPGAs y GPGPUs: Un artículo de revisión

Fajardo

Villar

Pedraza³

2013

ing.cienc.

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MSC:68M20 / PACS:93.85.Rt ResumenEste artículo hace una revisión entorno a los esfuerzos que actualmente se están realizando con el propósito de reducir el tiempo de cómputo de la MS. Nosotros introducimos los métodos más utilizados para realizar el proceso de Migración, así como también las dos arquitecturas computacionales que están ofreciendo mejores tiempos de procesamiento. Revisamos las implementaciones más representativas de este proceso sobre estas dos tecnologías y resumimos los aportes de cada una de estas investigaciones. El artículo finaliza con un análisis acerca de la dirección que deben tomar futuras investigaciones en esta área.Palabras clave: Evaluación del desempeño, FPGA, GPGPU, Métodos sís-micos de exploración, Migración Sísmica.

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FFT Implementation on a Streaming Architecture

Cited by 5 publications

References 9 publications

Challenges in exascale radio astronomy: Can the SKA ride the technology wave?

Challenges in exascale radio astronomy: Can the SKA ride the technology wave?

Amplitude Malformation in the IFFT Ocean Wave Rendering under the Influence of the Fourier Coefficient

Reducción de los tiempos de cómputo de la Migración Sísmica usando FPGAs y GPGPUs: Un artículo de revisión

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