CUDA与FPGA？ [英] CUDA vs FPGA?

问题描述

我开发的产品具有重型3D图形计算功能，在很大程度上最接近点和范围搜索。一些硬件优化将是有用的。虽然我不知道这个，我的老板（没有软件经验）主张FPGA（因为它可以定制），而我们的初级开发商主张GPGPU与CUDA，因为它便宜，热和开放。虽然我觉得我在这个问题上缺乏判断力，但我认为CUDA也是因为我担心灵活性，我们的产品仍然处于强劲的发展之中。

I am developing a product with heavy 3D graphics computations, to a large extent closest point and range searches. Some hardware optimization would be useful. While I know little about this, my boss (who has no software experience) advocates FPGA (because it can be tailored), while our junior developer advocates GPGPU with CUDA, because its cheap, hot and open. While I feel I lack judgement in this question, I believe CUDA is the way to go also because I am worried about flexibility, our product is still under strong development.

，重述这个问题，有什么理由去FPGA吗？还是有第三个选项？

So, rephrasing the question, are there any reasons to go for FPGA at all? Or is there a third option?

推荐答案

在与使用FPGA的人聊天之后，这是我得到的：

I investigated the same question a while back. After chatting to people who have worked on FPGAs, this is what I get:

• FPGA非常适合实时系统，可能太长。这不适用于您的情况;


• FPGA可以非常快速，特别适用于定义明确的数字信号处理用途（例如雷达数据），但好的是比昂贵和专业甚至专业的GPGPU;


• FPGA编程相当麻烦。由于有一个硬件配置组件来编译，它可能需要几个小时。

如果您可以使用这个工具，使CUDA为您工作，它可能是目前最好的选择。它肯定会比FPGA更灵活。

If you can make CUDA work for you, it's probably the best option at the moment. It will certainly be more flexible than a FPGA.

其他选项包括来自ATI的Brook，但直到发生大的事情，它不如CUDA那么好。之后，仍然有所有的传统HPC选项（x86 / PowerPC / Cell的集群），但它们都相当昂贵。

Other options include Brook from ATI, but until something big happens, it is simply not as well adopted as CUDA. After that, there's still all the traditional HPC options (clusters of x86/PowerPC/Cell), but they are all quite expensive.

希望有帮助。

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