Фильтры

Блоги

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
Автор: David S. (Blackbelt) Последнее обновление: 04.07.2019 - 20:00
Article

Caffe* Training on Multi-node Distributed-memory Systems Based on Intel® Xeon® Processor E5 Family

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:54
Article

基于英特尔® 至强™ 处理器 E5 产品家族的多节点分布式内存系统上的 Caffe* 培训

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:55
Article

Thread Parallelism in Cython*

Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Автор: Nguyen, Loc Q (Intel) Последнее обновление: 06.07.2019 - 16:30
Блоги

Big Datasets from Small Experiments

Автор: Andrey Vladimirov Последнее обновление: 04.07.2019 - 18:46
Блоги

Track Reconstruction with Deep Learning at the CERN CMS Experiment

Connecting the Dots
Автор: Последнее обновление: 12.12.2018 - 18:00
Article

Case Study: Optimized Code for Neural Cell Simulations

One of the Intel® Modern Code Developer Challenge winners, Daniel Falguera, describes many of the optimizations he implemented and why some didn't work.
Автор: Последнее обновление: 03.10.2019 - 07:55
Article

案例研究: 面向神经细胞模拟优化代码

Intel held the Intel® Modern Code Developer Challenge that had about 2,000 students from 130 universities in 19 countries registered to participate in the Challenge. They were provided access to Intel® Xeon Phi™ coprocessors to optimize code used in a CERN openlab brain simulation research project. In this article Daniel Vea Falguera (Modern Code Developer Challenge winner) shares how he...
Автор: Последнее обновление: 03.10.2019 - 07:56
Article

Intel Cluster Ready FAQ: Customer benefits

Q: Why should we select a certified Intel Cluster Ready system and registered Intel Cluster Ready applications?

Автор: Krotz-Vogel, Werner (Intel) Последнее обновление: 08.10.2019 - 18:20