As deep learning models have grown in complexity and size, the need for accelerated and high-performance computing is paramount. With the choice of multiple languages and frameworks, it is necessary for each developer to discern what is the optimal choicefor their specific requirements.
In this paper, we conduct a comprehensive comparative analysis of CUDA and OpenMP on the basis of:
- Programmability
- Scalability
- Performanceand Overheads
- Sieve of Eratosthenes
- Convolution Operation
- Bellman-Ford
- N-Queens and
- Kmeans Clustering