Vídeo

即使不用最新硬件也可实现最新AVX SIMD指令调优

向量化对于充分发挥现代处理器的全部潜能具有至关重要的作用。

Criado por Wei Du (Intel) Última atualização em 28/01/2019 - 00:20
Article

自动驾驶开发如何起步

从安全的路程到愉快的通勤,自动驾驶必将使生活和社会变得更美好。

随着汽车进入自主世界的中心,开发商被赋予创造创新和无缝的解决方案以快速响应市场需求并与市场需求一起增长的任务。 这在车辆和数据中心两方面都要求一些重大的资源。 英特尔已从消费者出发构建了一个生态系统。 利用这些工具,您将能创造——并且重新创造——驾驶的体验。

Criado por administrar Última atualização em 07/08/2019 - 20:09
Article

Как начать разработку решений для автоматизированного вождения автомобилей

От безопасных дорог до комфортных поездок на работу — автоматизированное вождение призвано изменить к лучшему жизнь обычных людей и всего общества.

Criado por administrar Última atualização em 07/08/2019 - 20:09
Vídeo

借助英特尔 Vectorization Advisor 优化 SIMD 代码

Criado por IDZSupport K. Última atualização em 17/01/2019 - 00:25
Article

准确预报各种天气:英特尔五步框架帮助实现代码现代化

天气预报是现代生活的一个重要方面,它可在出现恶劣天气状况时即时发出警报,从而帮助有效制定计划和安排物流,并可保护生命财产安全。 但是,准确预测长期的天气情况非常复杂,通常涉及到大量数据集,并且要求对代码进行优化以利用最高级的计算机硬件功能。

Criado por Última atualização em 30/09/2019 - 17:28
Article

Vectorization Advisor 助您一臂之力

Vectorization Advisor is like having a trusted friend look over your code and give you advice based on what he sees. As you’ll see in this article, user feedback on the tool has included, “there are significant speedups produced by following advisor output, I'm already sold on this tool!”
Criado por Última atualização em 02/10/2019 - 15:40
Article

Приводим данные и код в порядок: данные и разметка, часть 2

In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking 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.
Criado por David M. Última atualização em 15/10/2019 - 16:40
Article

整理您的数据和代码: 数据和布局 - 第 2 部分

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.
Criado por David M. Última atualização em 15/10/2019 - 16:40
Article

3D 同性声波有限差分波动方程代码:多核处理器实施与分析

有限差分是一个简单有效的数学工具,用于求解微分方程。在本文中,我们将利用明确的时间域有限差分求解同性声波 3D 波动方程。

Criado por Sunny G. (Intel) Última atualização em 15/10/2019 - 16:40