IBM Scientists Develop Algorithm to Accelerate Machine Learning Training
Channel: IBM Research
Date: 2017-12-05

IBM and EPFL scientists have developed a scheme for workloads where big data sets need to be trained quickly. In their paper they report on how their scheme learned to distinguish the difference between cats and dogs using a 30 Gigabyte training dataset in less than a 1 minute using a single GPU – a 10x speedup over existing methods for limited memory training. The results, which efficiently utilize the full potential of the GPU, are being presented at the Conference on Neural Information Processing Systems (NIPS) in Long Beach, California.

Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems, Celestine Dünner, Thomas Parnell, Martin Jaggi, https://arxiv.org/abs/1708.05357