In this video from SC16, Intel demonstrates how Altera FPGAs can accelerate Machine Learning applications with greater power efficiency. “The demo was put together using OpenCL design tools and then compiled to FPGA. From an end-user perspective, they tied it together using Intel MKL-DNN with CAFFE on top of that. This week, Intel announced the DLIA Deep Learning Inference Accelerator that brings the whole solution together in a box.”
Intel Furthers Machine Learning Capabilities
“Intel provided a wealth of machine learning announcements following the Intel Xeon Phi processor (formerly known as Knights Landing) announcement at ISC’16. Building upon the various technologies in Intel Scalable System Framework, the machine learning community can expect up to 38% better scaling over GPU-accelerated machine learning and an up to 50x speedup when using 128 Intel Xeon Phi nodes compared to a single Intel Xeon Phi node. The company also announced an up to 30x improvement in inference performance (also known as scoring or prediction) on the Intel Xeon E5 product family due to an optimized Intel Caffe plus Intel Math Kernel Library (Intel® MKL) package.”





