packing two single precision values into one

Question

I'm in labview working with very constrained ram. I have two arrays that require single precision since I need decimal points. However, single precision takes too much space for what I have, the decimal values I work with are within 0.00-1000.00.

Is there an intuitive way to pack these two arrays together so I can save some space? Or is there a different approach I can take?

Answer 1

If you need to represent 0.00 - 1000.00, you've got 100000 values. That cannot be represented in less than 17 (whole) bits. That means that to fit two numbers in, you'll need 34 bits. 34 bits is obviously more than you can fit in a 32 bit space. I suggest you try to limit your space of values. You could dedicate 11 bits to the integer value (0 - 1023) and 5 bits to the decimal value (0 to 0.96875 in chunks of 1/32 or 0.03125). Then you'll be able to fit two decimal values into one 32 bit space.

Just remember the extra bit manipulation you have to do for this is likely to have a small performance impact on your application.

Answer 2

First of all it would be good general advice to double check you've correctly understood how LabVIEW stores data in memory and whether any of your VI's are using more memory than they need to.

If you still need to squeeze this data into the minimum space, you could do something like:

• Instead of a 1D array of n values, use a 2D array of ceiling(n/16) x 17 U16's. Each U16 is going to hold one bit from each of 16 of your data values.
• To read value m from the array, get the 17 U16's from row m/16 of the array and get bit (m MOD 16) from each U16, then combine them to create the value you need.
• To write to the array, get the relevant 17 U16's, replace the relevant bit of each with the bits representing the new value, and replace the changed U16's in the array.

I guess this won't be fast but maybe you can optimise it for the particular operations you need to do on this data.

Alternatively, could you perhaps use some sort of data compression? I imagine that would work best if you can organise the data into 'pages' containing some set number of values. For example, you could take a 1D array of SGL, flatten it to a string, then apply the compression to the string, and store the compressed string in a string array. I believe OpenG includes zip tools, for example.