Efficient Histogram Algorithms for NVIDIA CUDA Compatible Devices

We present two efficient histogram algorithms designed for NVIDIA’s compute unified device architecture (CUDA) compatible graphics processor units (GPUs). Our algorithm can be used for parallel computation of histograms on large data-sets and for thousands of bins. Traditionally histogram computation has been difficult and inefficient on the GPU. This often means that GPU-based implementation of the algorithms that require histogram calculation as part of their computation, require to transfer data between the GPU and the host memory, which can be a significant bottleneck. Our algorithms remove the need for such costly data transfers by allowing efficient histogram calculation on the GPU. We show that the speed of histogram calculations can be improved by up to 30 times compared to a CPU-based implementation.