Q-Chem currently offers the possibility of accelerating RI-MP2 calculations using graphics processing units (GPUs). Currently, this is implemented for CUDA-enabled NVIDIA graphics cards only, such as (in historical order from 2008) the GeForce, Quadro, Tesla and Fermi cards. More information about CUDA-enabled cards is available at
It should be noted that these GPUs have specific power and motherboard requirements.
Software requirements include the installation of the appropriate NVIDIA CUDA driver (at least version 1.0, currently 3.2) and linear algebra library, CUBLAS (at least version 1.0, currently 2.0). These can be downloaded jointly in NVIDIA’s developer website:
We have implemented a mixed-precision algorithm in order to get better than single precision when users only have single-precision GPUs. This is accomplished by noting that RI-MP2 matrices have a large fraction of numerically “small” elements and a small fraction of numerically “large” ones. The latter can greatly affect the accuracy of the calculation in single-precision only calculations, but calculation involves a relatively small number of compute cycles. So, given a threshold value , we perform a separation between “small” and “large” elements and accelerate the former compute-intensive operations using the GPU (in single-precision) and compute the latter on the CPU (using double-precision). We are thus able to determine how much double-precision we desire by tuning the parameter, and tailoring the balance between computational speed and accuracy.
$molecule 0 1 c h1 c 1.089665 h2 c 1.089665 h1 109.47122063 h3 c 1.089665 h1 109.47122063 h2 120. h4 c 1.089665 h1 109.47122063 h2 -120. $end $rem METHOD rimp2 BASIS cc-pvdz AUX_BASIS rimp2-cc-pvdz CUDA_RIMP2 1 $end
$molecule 0 1 c h1 c 1.089665 h2 c 1.089665 h1 109.47122063 h3 c 1.089665 h1 109.47122063 h2 120. h4 c 1.089665 h1 109.47122063 h2 -120. $end $rem METHOD rimp2 BASIS cc-pvdz AUX_BASIS rimp2-cc-pvdz CUDA_RIMP2 1 USE_MGEMM 1 MGEMM_THRESH 10000 $end