Geforce gtx 970

We perform benchmark simulations on hardware systems that can be considered as standard equipment in a computational research lab. We did not attempt to use high performance computing facilities that, for most users, are available only for highly limited computing time and require an overhead in scheduling simulation jobs. We employ three computer server systems specified in Table 1, which were acquired between 2016 and 2022. The amount of investment at the time of purchase has been fairly stable on the order of $7, 000−$10, 000 depending on whether a state-of-the-art GPU was included. Servers S1 and S3 are equipped with GPUs. The GeForce GTX 970 (S1; NVIDIA, Santa Clara, USA) can now be considered a low-cost GPU in the price range of $300. The Quadro RTX A6000 (S3; NVIDIA, Santa Clara, USA) is one example of current state-of-the-art high-end GPUs, for which prices vary in the range of $3, 000−$5, 000. We use the job scheduler HTCondor (Thain et al., 2005 (link)) on all servers independently, with one job scheduler per server. We ensure acquisition of all cores and the complete GPU to a running job and prevent other jobs from execution till the running job is finished.

Movements of the right eye were recorded at 2000 Hz using the SR Research EyeLink 1000 Plus. Participants were asked to keep their head in the head support during the entire experiment.
The visual stimuli were presented using a computer running ‘SR Research Experiment Builder’ (version 1.10.1386) on a 64-bit Windows 7 Professional operating system. The computer contained an Intel Core i7-4790K Processor (@ 4.00 GHz) and NVIDIA GeForce GTX 970 graphics card. The stimuli were shown on a 24.5-inch BENQ monitor (XL2540) with a resolution of 1920 × 1080 pixels, and a display area of 531 × 298 mm. The refresh rate of the monitor was set to 144 Hz. The monitor was positioned 95 cm from the table edge. For a distance between the eyes and monitor of 91 cm, the monitor subtended horizontal and vertical viewing angles of 33° and 19°, respectively. The eye-tracking camera/IR light source was located at 65 cm from the head support. Participants wore closed-back headphones to block out ambient noise. There was no natural light in the room. The illuminance of the fluorescent lighting in the room near the experimental setup was around 400 lx, as measured with a Konica Minolta T-10MA illuminance meter.

The proposed system uses an RGB-D camera to scan the electrodes and anatomical features. Specifically, a Realsense camera software development kit was used to interface the RGB-D camera and acquire the scanned 3D points. A visualization toolkit and a point cloud library were used to visualize the processed data and handle the 3D points, respectively [22 ]. The software was executed in a workstation equipped with an Intel Core i7 CPU, 32 GB RAM, and NVIDIA GeForce GTX 970 GPU.