Computer Requirements


Make sure to get a computer with sufficient PCI/PCIe slots for the camera framegrabber cards (usually 2 cameras/cards for dual-view) plus whatever other peripherals you need.

Otherwise the main requirement having sufficiently fast disk write speed to handle the camera data. Depending on the use case, solid state drives (SSDs) and/or RAID0 with SSDs may or may not be required. Individual users should consider their requirements.

The sCMOS cameras used with diSPIM can generate 800 MB/sec (100 fps at 4 MP, 16 bits per pixel). However the maximum possible frame rate of the camera is not achieved for diSPIM.1) Typical maximum acquisition speeds are 1024×1024 at 50fps or 512×512 at 200 fps; both these situations both generate 100MB/sec. The average data rate, and hence hard drive speed requirement, is usually even less because most commonly acquisition occurs in bursts (i.e. there is time between successive time points) and a RAM buffer initially holds images so the hard drive needs to keep up with the average data rate. Usually only one camera works at a time, though there are schemes where both cameras could be used simultaneously and thus double the data rate or else multiple cameras could be used for simultaneous multi-channel recording.

100 MB/sec is typical for a magnetic hard drive. 300 MB/sec is typical for a single SSD. If the data rate is too high for a single SSD, use SSDs in RAID0 configuration (e.g. 4 SSDs in RAID0 can achieve >1 GB/s). Lately M.2 drives with PCIe interface with comparable speeds to a RAID0 with SSDs have become available and might be a good option. To benchmark your PC's hard drive write speed you can use Crystal Disk Mark. I'm pretty sure the relevant score to diSPIM acquisition is the “Seq” “Write” score (Sequential (Block Size=1MiB) Read/Write with single Thread), at least for Micro-manager software with typical acquisition settings.

Light sheet can generate lots of data very quickly, and it is important to have a plan to deal with the deluge. This often involves support from the institution's IT department. A helpful discussion of the challenges and options is the article Biologists need modern data infrastructure on campus.

Data Analysis

Some users do image analysis and processing on a separate workstation, others use the acquisition computer when it's not being used for acquisition.

Having lots of RAM can speed any analysis; ideally the entire dataset can be held in active memory. Ideally get a computer with CUDA-capable graphics card because some of the data analysis software can take advantage of it to speed the computation (OpenCL is a competing framework for GPU computation). This is a nascent area and depends on software support; many software developments data analysis are forthcoming so it's hard to say exactly what will be the best hardware in the long run.

Micro-Manager 2.0 has a helpful ability to reslice data into the “lab frame” which is helpful especially for stage scanning data. The GPU version of the algorithm can operate on datasets up to 1/4 of the GPU memory, e.g. 2 GB datasets can be processed on a GPU with 8 GB of working memory.

Specific suggestions

In 2018 ASI has successfully used use a Dell Precision 7920 tower with 6-core Xeon CPU, one SSD for the OS/applications and a RAID0 drive with 4 SSDs for data, 64 GB RAM, and Nvidia P2000. This has spare PCIe slots even with 2 camera framegrabber cards, the graphics card, and RAID controller.

Previously (~2016?) ASI has successfully used Dell Precision T3600 with 8-core Xeon CPU, 4x SSDs in RAID0, 64 GB RAM, Nvidia Quadro K4200, and enough PCIe slots (2 camera framegrabber cards, graphics card, and RAID controller).

Light sheet illumination only occurs during global exposure, and camera-limited frame rates occur without any global exposure time.