‘Controlled Hogwild with Arbitrary Order of Synchronization’ (CHAOS) – a Parallelization Method for Training Convolutional Neural Networks. Up to x100 speedup on Xeon Phi and x50 on Intel Core i5: https://arxiv.org/abs/1702.07908 [PDF]
Paper authors: Andre Viebke, Suejb Memeti, Sabri Pllana, Ajith Abraham
Abstract: “Deep learning is important for many modern applications, such as, voice recognition, face recognition, autonomous cars, precision medicine, or computer vision. We have presented CHAOS that is a parallelization scheme to speed up the training process of Convolutional Neural Networks. CHAOS can exploit both thread- and SIMD-parallelism of Intel Xeon Phi co-processor. Moreover, we have described our performance prediction model, which we use to evaluate our parallelization solution and infer the performance on future architectures of the Intel Xeon Phi.”
