With VR is accepted by more and more people, more and more game companies begin to develop VR games.
Intel GPA is a suite of graphics performance optimization tools that enables developers to visualize, isolate and resolve graphics performance issues. Improve the performance of your games with the performance analysis methods presented in this article.
With the release of Android 5.0 Lollipop*, an innovative default runtime environment was introduced, called ART* (short for Android RunTime). It includes a number of enhancements that improve performance. In this paper, we introduce some of the new features in ART, benchmark it against the previous Android Dalvik* runtime, and share five tips for developers that can further improve application...
The Kyoto University team recognized that the performance of the open source Theano C++ multi-core code could be significantly improved. They worked with Intel to improve Theano multicore performance using a dual-socket Intel® Xeon®processor based system as the next generation Intel® Xeon Phi™ processors were not available at that time
This series of two articles discusses how data and memory layout affect performance and suggests specific steps to improve software performance. The basic steps shown in these two articles can yield significant performance gains. These two articles are designed at an intermediate level. It is assumed the reader desires to optimize software performance using common C, C++ and Fortran* programming...
This article demonstrates how using the proper texture format can improve OpenGL performance—in particular, using native texture formats will give game developers the best OpenGL performance. Accompanying the article is a C++ example application that shows the effects on rendering performance when using a variety of texture formats.
This article discusses machine learning and describes a machine learning method/algorithm called Naïve Bayes (NB) . It also describes how to use Intel® Data Analytics Acceleration Library (Intel® DAAL)  to improve the performance of an NB algorithm.
This article discusses why using a texture rather than an image can improve OpenGL rendering performance. It is accompanied by a simple C++ application that alternates between using a texture and using an image. The purpose of this application is to show the effect on rendering performance (milliseconds per frame) when using the two techniques.
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.
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.