The gaming industry has seen great strides in game complexity recently. Game developers are challenged to create increasingly compelling games. This series explores important Artificial Intelligence (AI) concepts and how to optimize them for multi-core.
Designing AI for Games. Intelligent agents need to identify points of interest in the game world. This article shows how to identify and optimize points of interest and provides ways of organizing them for multi-threading.
This Technology Insight will demonstrate how to optimize data analytics and machine learning workloads for Intel® Architecture based data center platforms. Speaker: Pradeep Dubey Intel Fellow, Intel Labs Director, Parallel Computing Lab, Intel Corporation
While there are many different programming models for the Intel® Xeon Phi™ coprocessor (code-named Knights Corner (KNC)), this paper lists the more prevalent KNC programming models and further discusses some of the necessary changes to port and optimize KNC models for the Intel® Xeon Phi™ processor x200 self-boot platform.
This year marks the tenth anniversary of Intel® Threading Building Blocks (Intel® TBB).
This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.