What Challenges are Associated with GPU Accelerators in Nanotechnology?
Despite their advantages, there are several challenges associated with the use of GPU accelerators in nanotechnology:
Programming Complexity: Developing software to run on GPUs can be more complex compared to CPUs, requiring specialized knowledge of parallel programming languages like CUDA or OpenCL. Data Transfer Bottlenecks: Transferring data between the CPU and GPU can be a bottleneck, potentially negating some of the performance gains. Hardware Costs: High-performance GPUs can be expensive, which may be a barrier for some research institutions.
