Texture memory (now called read only data cache) would probably be a choice worth exploring, although not for the interpolation benefits. It supports 32 bit reads without reading beyond this amount. However, you're limited to 48K in total. For Kepler (compute 3.x) this is quite simple to program now.
Global memory, unless you configure it in 32 bit mode, will often drag in 128 bytes for each thread, hugely multiplying what is actually data needed from memory as you (apparently) can't coalesce the memory accesses. Thus the 32 bit mode is probably what you need if you want to use more than 48K (you mentioned 40K).
Thinking of coalescing, if you were to access a set of values in series from these tables, you might be able to interleave the tables such that these combinations could be grouped and read as a 64 or 128 bit read per thread. This would mean the 128 byte reads from global memory could be useful.
The problem you will have is that you're making the solution memory bandwidth limited by using lookup tables. Changing the L1 cache size (on Fermi / compute 2.x) to 48K will likely make a significant difference, especially if you're not using the other 32K of shared memory. Try texture memory and then global memory in 32 bit mode and see which works best for your algorithm. Finally pick a card with a good memory bandwidth figure if you have a choice over hardware.