I’m playing with CUDA in order to find out if it’s suitable for my needs. Most of projects of SDK work just fine on my hardware (8500 GT), but BlackScholes options pricing sample constantly produces the following output:
…allocating CPU memory for options.
…allocating GPU memory for options.
…generating input data in CPU mem.
…copying input data to GPU mem.
Data init done.
Executing GPU kernel…
Options count : 40000000
BlackScholesGPU() time: 1017.946106 msec
Options per second : 3.929481E+007
Reading back GPU results…
Checking the results…
…running CPU calculations.
Comparing the results…
L1 norm: 1.000000E+000
Max absolute error: 9.581588E+001
…releasing GPU memory.
…releasing CPU memory.
Looks like the accuracy of computations is bad in case of this sample … Why can this happen ? Replacing of fast routines (__expf, __logf) with normal ones (expf, logf) does not help.
Thanks in advance.