In general, the GPU memory should not be an arbitrary limitation on the size of data for algorithms.
一般来说，在GPU内存不应该对数据进行算法的大小任意的限制。
Every vertical blank, the hypervisor DMAs this buffer to the GPU memory, and then flips the GPU's visible page to the new data synchronously with the vertical blank signal.
对于垂直方向上的每个空格来说，管理程序都会采用 DMA 方式将自己的缓冲区读到GPU 的内存中，然后将 GPU的可视页刷新为与垂直空格信号同步的数据。
Each CUDA-capable GPU node includes local DDR3 SDRAM as well as a 16-lane PCI Express? gen2 interface to the system backplane, providing maximum data throughput direct to GPU memory.
每个CUDAGPU节点包括本地的DDR3SDRAM以及一个16通道PCI二代系统的背板接口，直接向GPU内存提供最大的数据流量。
The GPU memory could be considered to be a "cache" of data that the GPU is currently operating on, but many GPU algorithms are designed to operate on more data than can fit in the "cache".
的GPU内存可以被认为是一个“缓存”，GPU目前经营上的数据，但许多GPU算法的设计有更多的数据比操作可以在“缓存”。
This might sound simple, but there are a lot of design decisions around making sure that GPU memory is not allocated without the user asking for it and still allowing people to build what they want.
这听起来貌似很简单，但是这背后有着大量的设计决定以确保GPU内存没有分配给不需要之人，且仍然能够允许人们构造他们之所想。
The window server provides a region of Shared memory to clients for drawing and then composites this into the frame buffer (on the GPU).
窗口服务器为客户提供了一块共用内存区域用来绘图，然后(用gpu)将其混合为帧缓冲。
While that little port isn't a big problem for most visual jobs, it's a hassle for parallel computing that works the CPU, GPU, and memory all in close association.
虽然这个小小的接口对大部分显示工作来说并不是什么大问题，但它却无法应付CPU、GPU和内存紧密结合的并行运算。
Instead of using the CPU to display graphics, Vista USES the GPU, which puts a strain on memory.
Vista使用GPU而不是CPU来显示图像，这给内存造成了压力。
The bottleneck is the memory on board GPU processors: it's fast, but not fast enough.
GPU处理器的瓶颈在于搭配的显存：虽然很快，但还是不够快。
When you create a buffer, you just get a pointer to it, and that's the same memory that the GPU sees.
当你创建一个缓冲区时，得到一个指针，GPU也看到了同样的内存。
When you create a buffer, you just get a pointer to it, and that's the same memory that the GPU sees.
当你创建一个缓冲区时，得到一个指针，GPU也看到了同样的内存。
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