Takashige Sugie

Computer generated holography using a graphics processing unit

We have applied the graphics processing unit (GPU) to computer generated holograms (CGH) to overcome the high computational cost of CGH and have compared the speed of a GPU implementation to a standard CPU implementation. The calculation speed of a GPU (GeForce 6600, nVIDIA) was found to be about 47 times faster than that of a personal computer with a Pentium 4 processor. Our system can realize real-time reconstruction of a 64-point 3-D object at video rate using a liquid-crystal display of resolution 800x600.

Special-purpose computer HORN-5 for a real-time electroholography

In electroholography, a real-time reconstruction is one of the grand challenges. To realize it, we developed a parallelized high performance computing board for computer-generated hologram, named HORN-5 board, where four large-scale field programmable gate array chips were mounted. The number of circuits for hologram calculation implemented to the board was 1,408. The board calculated a hologram at higher speed by 360 times than a personal computer with Pentium4 processor. A personal computer connected with four HORN-5 boards calculated a hologram of 1,408 x 1,050 made from a three-dimensional object consisting of 10,000 points at 0.0023 s. In other words, beyond at video rate (30 frames / s), it realized a real-time reconstruction.

HORN-6 special-purpose clustered computing system for electroholography.

We developed the HORN-6 special-purpose computer for holography. We designed and constructed the HORN-6 board to handle an object image composed of one million points and constructed a cluster system composed of 16 HORN-6 boards. Using this HORN-6 cluster system, we succeeded in creating a computer-generated hologram of a three-dimensional image composed of 1,000,000 points at a rate of 1 frame per second, and a computer-generated hologram of an image composed of 100,000 points at a rate of 10 frames per second, which is near video rate, when the size of a computer-generated hologram is 1,920 x 1,080. The calculation speed is approximately 4,600 times faster than that of a personal computer with an Intel 3.4-GHz Pentium 4 CPU.

Numerical calculation library for diffraction integrals using the graphic processing unit: the GPU-based wave optics library

In optics, several diffraction integrals, such as the angular spectrum method and the Fresnel diffraction, are used for calculating scalar light propagation. The calculation result provides us with the optical characteristics of an optical device, the numerical reconstruction image from a hologram, and so forth. The acceleration of the calculation commonly uses the fast Fourier transform; however, in order to analyze a three-dimensional characteristic of an optical device and compute real-time reconstruction from holograms, recent computers do not have sufficient computational power. In this paper, we develop a numerical calculation library for the diffraction integrals using the graphic processing unit (GPU), the GWO library, and report the performance of the GWO library. The GPU chip allows us to use a highly parallel processor. The maximum computational speed of the GWO library is about 20 times faster than a personal computer.

Special-purpose computer for holography HORN-3 with PLD technology

Abstract We have designed and built a special-purpose computer for holography, HORN-3 (HOlographic ReconstructioN) using PLD (Programmable Logic Device) technology. We could integrate a pipeline to calculate hologram into one PLD chip, so that we can readily parallelize the system. By mounting two of the PLD chips on a PCI (Peripheral Component Interconnect) universal board, HORN-3 calculates light intensity at high speed of about 1.2 G flops. The cost of HORN-3 board is 200,000 Japanese yen (1600 US dollar). We obtained 1024× 768 grids hologram from a virtual 3D-image composed of 2500 points in about 60 sec with the HORN-3 system.

Random phase-free kinoform for large objects.

We propose a random phase-free kinoform for large objects. When not using the random phase in kinoform calculation, the reconstructed images from the kinoform are heavy degraded, like edge-only preserved images. In addition, the kinoform cannot record an entire object that exceeds the kinoform size because the object light does not widely spread. In order to avoid this degradation and to widely spread the object light, the random phase is applied to the kinoform calculation; however, the reconstructed image is contaminated by speckle noise. In this paper, we overcome this problem by using our random phase-free method and error diffusion method.

Special purpose computer system with highly parallel pipelines for flow visualization using holography technology

Abstract We have designed a PC cluster system with special purpose computer boards for visualization of fluid flow using digital holographic particle tracking velocimetry (DHPTV). In this board, there is a Field Programmable Gate Array (FPGA) chip in which is installed a pipeline for calculating the intensity of an object from a hologram by fast Fourier transform (FFT). This cluster system can create 1024 reconstructed images from a 1024 × 1024 -grid hologram in 0.77 s. It is expected that this system will contribute to the analysis of fluid flow using DHPTV.

Color computer-generated hologram generation using the random phase-free method and color space conversion

We propose two calculation methods of generating color computer-generated holograms (CGHs) with the random phase-free method and color space conversion in order to improve the image quality and accelerate the calculation. The random phase-free method improves the image quality in monochrome CGH, but it is not performed in color CGH. We first aimed to improve the image quality of color CGH using the random phase-free method and then to accelerate the color CGH generation with a combination of the random phase-free method and color space conversion method, which accelerates the color CGH calculation due to down-sampling of the color components converted by color space conversion. To overcome the problem of image quality degradation that occurs due to the down-sampling of random phases, the combination of the random phase-free method and color space conversion method improves the quality of reconstructed images and accelerates the color CGH calculation. We demonstrated the effectiveness of the proposed method in simulation, and in this paper discuss its application to lensless zoomable holographic projection.

A special-purpose computer for exploring similar protein sequences by the dynamic programming method

We built a special-purpose computer for exploring similar protein sequences by the dynamic programming method, BIOLER-1 (BIOLogical sequence explorER). It can compute a complete similarity between two protein sequences which have less than 1024 amino acids. We integrated the system on a PLD (Programmable Logic Device) chip, APEX EP20K300EQC240-1 (300,000 gates) by Altera corporation. It is mounted on the 32 bit PCI (Peripheral Component Interconnect) bus board which is connected to a personal computer. The performance is 3564 MIPS (Million Instructions Per Second) which is three times faster than a personal computer with Pentium4 at 1.8 GHz. BIOLER-1 showed us the effectiveness in the field of biological sequence analysis.

A special-purpose computer for exploring similar biological sequences: Bioler-2 with multi-pipeline and multi-sequence architecture

Abstract We developed a special-purpose computer for exploring similar biological sequences by Smith–Waterman method, Bioler-2 (BIOLogical sequence explorER). It can compute a complete similarity score between two biological sequences which have less than 10,000 characters. We integrated the system on two FPGA (Field Programmable Gate Array) chips, XC2V6000 (6M gates) by Xilinx corporation. They are mounted on the 32 bit PCI (Peripheral Component Interconnect) bus card which is connected to the host computer. The performance of Bioler-2 is 142 times faster than a general-purpose computer installed the Linux kernel version 2.4.25 compiled by gcc (Gnu Compiler Collection) version 3.3.3 with Pentium4 enabled hyper threading technology at 3.2 GHz. Bioler-2 is effective in the biological sequence analysis.