Tasks are a lightweight alternative to threads that provide faster startup and shutdown times, better load balancing, an efficient use of available resources, and a higher level of abstraction.
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.
This tutorial shows how to install Offload over Fabric (OoF) software on 2nd generation Intel® Xeon Phi™ processor, configure the hardware, test the basic configuration, and enable OoF
如今，多核处理器已经在 PC 中普及，内核数量不断增长，软件工程师必须适应这种情况。通过学习如何处理潜在的性能瓶颈和并发性问题，工程师可以使他们的代码适应未来，以无缝处理添加到消费者系统的额外内核。
Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
This article identifies some of these challenges and illustrates strategies for addressing them while maintaining parallel performance.
In this tutorial, we demonstrate some possible ways to optimize an application to run on the Intel® Xeon Phi™ processor
Financial service customers need to improve financial algorithmic performance for models such as Monte Carlo, Black-Scholes, and others. SIMD programming can speed up these workloads. In this paper, we perform data layout optimizations using two approaches on a Black-Scholes workload for European options valuation from the open source Quantlib library.
Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...
学习如何在英特尔® 至强融核™ 处理器中使用 MPI-3 共享内存