cuda
- 网络统一计算设备架构(Compute Unified Device Architecture)；Common Unified Device Architecture；统一计算架构
cudacuda
统一计算设备架构(Compute Unified Device Architecture)
本文采用统一计算设备架构（CUDA）[8]进行PPI算法优化实现。CUDA是一种将GPU作为数据并行计算设备的软硬件体系。
Common Unified Device Architecture
...好的 GPGPU 的使用而受到影响。ATI 的 Stream 技术和 NVIDIA 的 Common Unified Device Architecture (CUDA) 架构都是 …
统一计算架构
本文设计并实现了GPU平台下，基于统一计算架构(CUDA)的并行灰度模型，可应用于大规模星模拟器的快速灰度模拟。首先分 …
流处理器
差别不是很大，主要是流处理器（CUDA）数量不同，频率也有点不同。性能相差20%-30%。
统一设备架构(Computer Unified Device Architecture)
基于统一设备架构(CUDA)的通用图形处理器(GPGPU)具有强大的数据处理能力与高速计算性能,可将图形处理器的并行计算能 …
1
David talked about expanding CUDA other hardware vendors, and the fact that this is going to require them to implement support for C.
David谈到想其他硬件厂商推广CUDA的事情，并要求他们实现对C的支持。
2
So what will it take to make CUDA a standard, or at least the ability to run general computing tasks written in C on a GPU?
那么是否会让CUDA成为业界标准，或者至少是让GPU运行C代码的通用计算任务？
3
CUDA for C and Brook+ will likely have more of a place in just trying out ideas before settling on a final direction.
采用CUDA的C和布鲁克+将可能有更多的地方只是尝试的想法解决之前，就最后的方向发展。
4
This example shows the parallel prefix sum (also known as " scan" ) of an efficient CUDA implementation of the approach.
本实例展示了并行前缀求和（也称作“scan”）的一种高效的CUDA实施途径。
5
Multiple NPN240s can be linked to single or multiple hosts to create multi-node CUDA GPU clusters capable of thousands of GFLOPS.
多个NPN240处理器可以链接到一个或多个主机，建立多节点CUDAGPU集群，峰值可达数千GFLOPS。
6
Following this, we moved the discussion towards CUDA, as it seemed like a natural progression.
接着，我们很自然地把话题转向了CUDA。
7
In fact, CUDA-based parallel computing has widely been accepted by research community and industry, and is developing rapidly.
事实上，基于CUDA的并行计算已经广泛地被科研界和产业界认可，正在迅速发展。
8
When using CUDA , we recommend you always install the latest version of the driver available from the NVIDIA corporate website.
当使用CUDA时，我们建议您总是使用从NVIDIA官方网站上下载的最新显卡驱动。
9
Both Brook+ and CUDA for C hide the complexity of setting up the hardware by allowing the driver to handle the details.
这布鲁克+和采用CUDA的C隐藏的复杂性，建立了硬件，让司机来处理的细节。
10
After experiments, comparing CPU' s computing power can be found, CUDA' s ability to process data in parallel is very strong.
在经过实验之后，对比CPU的计算能力可以发现，CUDA在并行处理数据的能力非常强大。
11
We do take every opportunity to discuss the ability to run CUDA with anyone who's interested.
但我们的确在抓紧每个机会与那些对CUDA感兴趣的人讨论运行CUDA的能力问题。
12
Achieve a highly paralleled algorithm to calculate the simplification error of triangular meshes by using CUDA.
利用CUDA实现了高度并行化的网格模型简化误差计算算法。
13
The CUDA driver and Toolkit installation are required before running the precompiled examples or compiling the example source code.
必需安装CUDA驱动和CUDA工具包，此后才可运行预编译的例程或编译样例源代码。
14
Beyond that, CUDA for C has done really well in the HPC (high performance computing) space, but it hasn't caught on in the consumer space.
除此之外，采用CUDA的C做了很好的高性能混凝土（高性能计算）的空间，但还没有陷入对消费空间。
15
In this paper, we implement an efficient matrix multiplication on GPU using NVIDIA's CUDA.
本文使用NVIDIA的CUDA在GPU上实现了一个高效的矩阵乘法。
16
CUDA? technology and multi-core CPUs supporting technology, the converting speed is 6X faster now.
CUDA技术？技术和多核心CPU的支持技术，转换速度更快了6倍。
17
For how to use CUDA implement Neural Network, and use it for processing image in GPU.
文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上。
18
CUDA 2. 2 Beta is now available to registered CUDA Developers.
2Beta测试版可供已注册的CUDA开发人员下载。
19
Something that could never happen with ether CUDA or Brook+.
这决不可能发生乙醚CUDA上或小溪+。
20
Fixed The picture would become green during an output using CUDA . If this problem occurs again an error arises.
使用CUDA输出时画面会变绿，且如果此问题再次发生则出现未知错误。