I installed the CUDA toolkit and ran the sample CUDA code as instructed on that blog.
optirun ./deviceQuery
[deviceQuery] starting...
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Found 1 CUDA Capable device(s)
Device 0: "GeForce GT 555M"
CUDA Driver Version / Runtime Version 4.10 / 4.10
CUDA Capability Major/Minor version number: 2.1
Total amount of global memory: 2048 MBytes (2147155968 bytes)
( 3) Multiprocessors x (48) CUDA Cores/MP: 144 CUDA Cores
GPU Clock Speed: 1.35 GHz
Memory Clock rate: 900.00 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 262144 bytes
Max Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536,65535), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(16384) x 2048, 2D=(16384,16384) x 2048
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 32768
Warp size: 32
Maximum number of threads per block: 1024
Maximum sizes of each dimension of a block: 1024 x 1024 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 65535
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): Yes
Device PCI Bus ID / PCI location ID: 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 4.10, CUDA Runtime Version = 4.10, NumDevs = 1, Device = GeForce GT 555M
[deviceQuery] test results...
PASSED
Press ENTER to exit...
optirun ./nbody
[nbody] starting...
Run "nbody -benchmark [-n=<numBodies>]" to measure perfomance.
-fullscreen (run n-body simulation in fullscreen mode)
-fp64 (use double precision floating point values for simulation)
-numdevices=N (use first N CUDA devices for simulation)
> Windowed mode
> Simulation data stored in video memory
> Single precision floating point simulation
> 1 Devices used for simulation
> Compute 2.1 CUDA device: [GeForce GT 555M]
Then I tried running FlaCuda and FlacCL without --opencl-platform but I got the same result. I'm sure it's something silly, there's no good reason your apps can't run on my setup.