Seems kind of like a blanket statement to make if you have not investigated this for yourself. So let me give you some example use cases. Decompression for pro

Seems kind of like a blanket statement to make if you have not investigated this for yourself. So let me give you some example use cases. Decompression for processing: We can roundtrip decompress 8 byte integers RRleDeltaRle 4x on an AWS g2.2xlarge faster when we use the GPU. This includes sending the data TO the GPU and brining it back. Our decompression segments on CPU were set up so that every thread was processing a segment to be decompressed so we were using every avaiable thread at about 100%. Sorting data: Here the difference can be startling. On an aws g2.2xlarge we are able to sort orders of magnitude faster than you can on GPU. Checkout thrust to run some exmaples http://docs.nvidia.com/cuda/thrust/#axzz4K7CRY352 http://docs.nvidia.com/cuda/thrust/#axzz4K7CRY352 A few modifications there can let you run this with both and NVIDIA backend and one that runs on CPU threads. It will run orders of magnitude faster on GPU than CPU on a small gpu instance on amazon. Even a laptop gpu would still outperform the cpu sorting capacity by at least an order of magnitude.