The Data Block
When data is acquired, it must be temporarily stored in computer memory. The memory required for data storage depends on several factors. For example, if you are acquiring data from an analog input device, then the required memory depends on the number of channels that data is being acquired from, the sampling rate, and the size of each sample.
The Data Acquisition Toolbox allocates memory in terms of data blocks. A data block is defined as the smallest "slice" of memory that can be usefully manipulated by the data acquisition engine. For example, acquired data is logged to a disk file using an integral number of data blocks.
The total memory allocated is given by the product of two variables: the data block size and the number of data blocks. The total allocated memory is often referred to as a buffer. A representation of allocated memory using several data blocks is shown below where block 1 is the first allocated block and block n is the last allocated block.
The Data Acquisition Toolbox strives to make memory allocation as simple as possible. For this reason, the default data block size and number of blocks are automatically calculated by the engine. This calculation is based on the parameters of your acquisition and is meant to apply to most common data acquisition applications. Additionally, as data data is acquired, the number of blocks dynamically increases such that sufficient total memory is allocated to (at least) store the data to be acquired per trigger. However, the engine cannot guarantee that the appropriate block size, number of blocks, or total memory is allocated under these conditions:
You are free to override the memory allocation policy used by the engine and manually change the block size and number of blocks at ant time. However, you should do so only after careful consideration since system performance may be adversely affected, which may result in lost data.
Acquired data that is stored to memory must be extracted in a timely way. If not, the data is overwritten and permanently lost. Managing acquired data is described in Chapter 4, "Managing Acquired Data."
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