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Hydra image processor: 5-D GPU image analysis library with MATLAB and python wrappers.
Bioinformatics ( IF 4.4 ) Pub Date : 2019-12-15 , DOI: 10.1093/bioinformatics/btz523
Eric Wait 1 , Mark Winter 1 , Andrew R Cohen 1
Affiliation  

SUMMARY Light microscopes can now capture data in five dimensions at very high frame rates producing terabytes of data per experiment. Five-dimensional data has three spatial dimensions (x, y, z), multiple channels (λ) and time (t). Current tools are prohibitively time consuming and do not efficiently utilize available hardware. The hydra image processor (HIP) is a new library providing hardware-accelerated image processing accessible from interpreted languages including MATLAB and Python. HIP automatically distributes data/computation across system and video RAM allowing hardware-accelerated processing of arbitrarily large images. HIP also partitions compute tasks optimally across multiple GPUs. HIP includes a new kernel renormalization reducing boundary effects associated with widely used padding approaches. AVAILABILITY AND IMPLEMENTATION HIP is free and open source software released under the BSD 3-Clause License. Source code and compiled binary files will be maintained on http://www.hydraimageprocessor.com. A comprehensive description of all MATLAB and Python interfaces and user documents are provided. HIP includes GPU-accelerated support for most common image processing operations in 2-D and 3-D and is easily extensible. HIP uses the NVIDIA CUDA interface to access the GPU. CUDA is well supported on Windows and Linux with macOS support in the future.

中文翻译:

Hydra图像处理器:具有MATLAB和python包装器的5D GPU图像分析库。

小结现在,光学显微镜可以以很高的帧速率捕获五个维度的数据,每个实验产生TB级的数据。五维数据具有三个空间维(x,y,z),多个通道(λ)和时间(t)。当前的工具非常耗时,并且不能有效地利用可用的硬件。hydra图像处理器(HIP)是一个新的库,提供可从包括MATLAB和Python在内的解释语言访问的硬件加速图像处理。HIP自动在系统和视频RAM之间分配数据/计算,从而允许硬件加速处理任意大图像。HIP还可以在多个GPU之间最佳地划分计算任务。HIP包括新的内核重新规范化,可减少与广泛使用的填充方法相关的边界效应。可用性和实现HIP是根据BSD 3-条款许可发布的免费开源软件。源代码和已编译的二进制文件将在http://www.hydraimageprocessor.com上进行维护。提供了所有MATLAB和Python接口以及用户文档的全面描述。HIP包括GPU加速支持,可支持2-D和3-D中的大多数常见图像处理操作,并且易于扩展。HIP使用NVIDIA CUDA接口访问GPU。CUDA将来会在Windows和Linux上得到很好的支持,并带有macOS支持。HIP包括GPU加速支持,可支持2-D和3-D中的大多数常见图像处理操作,并且易于扩展。HIP使用NVIDIA CUDA接口访问GPU。CUDA将来会在Windows和Linux上得到很好的支持,并带有macOS支持。HIP包括GPU加速支持,可支持2-D和3-D中的大多数常见图像处理操作,并且易于扩展。HIP使用NVIDIA CUDA接口访问GPU。CUDA将来会在Windows和Linux上得到很好的支持,并带有macOS支持。
更新日期:2020-01-13
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