GPGPU 是黑客吗？
几天前我开始研究 GPGPU，并成功实现了具有良好性能的胆囊因式分解，并且我参加了一个高性能计算会议，其中有人说“GPGPU 是一个 Hack”。
我仍然很困惑这是什么意思以及为什么他们说它是黑客。有人说这是黑客行为，因为你将问题转换为矩阵并对其进行运算。但我仍然很困惑，人们是否认为这是黑客攻击，或者如果是，那么为什么？
谁能帮助我，为什么他们称其为黑客，而我发现它没有任何问题。
I had started working on GPGPU some days ago and successfully implemented cholesky factorization with good performacne and I attended a conference on High Performance Computing where some people said that "GPGPU is a Hack".
I am still confused what does it mean and why they were saying it hack. One said that this is hack because you are converting your problem into a matrix and doing operations on it. But still I am confused that does people think it is a hack or if yes then why?
Can anyone help me, why they called it a hack while I found nothing wrong with it.
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出现这种观点的一个可能原因是 GPU 最初并不是用于通用计算。此外，GPU 编程不太传统，更硬核，因此更有可能被视为黑客行为。
“你把问题转化为矩阵”的观点根本不合理。无论您通过编写代码解决什么任务，您都会选择合理的数据结构。对于 GPU 矩阵可能是最合理的数据结构，这不是黑客，而是使用它们的自然选择。
不过我认为 GPGPU 的普及只是时间问题。人们只需要习惯这个想法。毕竟谁关心计算机的哪个单元运行该程序呢？
One possible reason for such opinion is that the GPU was not originally intended for general purpose computations. Also programming a GPU is less traditional and more hardcore and therefore more likely to be perceived as a hack.
The point that "you convert the problem into a matrix" is not reasonable at all. Whatever task you solve with writing code you choose reasonable data structures. In case of GPU matrices are likely the most reasonable datastructures and it's not a hack but just a natural choice to use them.
However I suppose that it's a matter of time for GPGPU becoming widespread. People just have to get used to the idea. After all who cares which unit of the computer runs the program?
在 GPU 上，高效的内存访问对于实现最佳性能至关重要。这通常涉及重构甚至选择全新的算法和数据结构。这就是为什么 GPU 编程会被视为黑客行为的原因。
其次，调整现有算法以在 GPU 上运行本身并不科学。一些 GPU 算法相关论文的科学贡献相对较低，导致人们对 GPU 编程被视为严格的“工程”的负面看法。
On the GPU, having efficient memory access is paramount to achieving optimal performance. This often involves restructuring or even choosing entirely new algorithms and data structures. This is reason why GPU programming can be perceived as a hack.
Secondly, adapting an existing algorithm to run on the GPU is not in and of itself science. The relatively low scientific contribution of some GPU algorithm-related papers has led to a negative perception of GPU programming as strictly "engineering".
显然，只有说这句话的人才能确切地说出他为什么这么说，但是，这是我的看法：
至于评论“你正在将问题转换为矩阵并对其进行运算”，我认为这表明了很多无知。几乎所有高性能计算都符合这一描述！
Obviously, only the person who said that can say for certain why he said it, but, here's my take:
As for the comment "you are converting your problem into a matrix and doing operations on it", I think that shows a lot of ignorance. Virtually ALL of high-performance computing fits that description!
过去几年以及未来几年 GPGPU 的主要问题之一是针对任意任务对其进行编程并不容易。直到 DX10 之前，GPU 之间还没有整数支持，并且分支仍然很差。在这种情况下，为了获得最大收益，您必须以一种非常尴尬的方式编写代码，以从 GPU 中获取各种效率增益。这是因为您运行的硬件仍然专用于处理多边形和纹理，而不是抽象的并行任务。
显然，这就是我的看法，YMMV
One of the major problems in GPGPU for the past few years and probably for the next few is that programming them for arbitrary tasks was not very easy. Up until DX10 there was no integer support among GPUs and branching is still very poor. This is very much a situation where in order to get maximum benefit you have to write your code in a very awkward manner to extract all sorts of efficiency gains from the GPU. This is because you're running on hardware that is still dedicated to processing polygons and textures, rather than abstract parallel tasks.
Obviously, thats my take on it and YMMV
GPGPU 让人回想起数学协处理器的时代。 hack 是解决冗长问题的捷径。 GPGPU 是一种黑客行为，就像 IPV4 之上的 NAT 是一种黑客行为一样。就像网络一样，随着我们尝试做得更多，计算问题变得越来越大，GPGPU 是一个有用的临时解决方案，无论它是留在核心 CPU 芯片之外并具有单独的胡思乱想的 API，还是通过 API 或制造吸入 CPU，都取决于路径发现者。
The GPGPU harks back to the days of the math co-processor. A hack is a shortcut to solving a long winded problem. GPGPU is a hack just like NAT on top of IPV4 is a hack. Computational problems just like networks are getting bigger as we try to do more, GPGPU is an useful interim solution, whether it stays outside the core CPU chip and has separate cranky API or gets sucked into the CPU via API or manufacture is up to the path finders.
我想他的意思是使用 GPGPU 迫使您重新构建您的实现，以便它适合硬件，而不是问题域。优雅的实现应该适合后者。
请注意，“hack”一词可能有几种不同的含义：
http://www.urbandictionary.com/define.php?term=hack
I suppose he meant that using GPGPU forced you to restructure your implementation, so that it fitted the hardware, not the problem domain. Elegant implementation should fit the latter.
Note, that the word "hack" may have several different meanings:
http://www.urbandictionary.com/define.php?term=hack