PAMELA: a Panoramic Approach to the Many-CorE LAndsape - from end-user to end-device: a holistic game-changing approach

在过去的十年里，计算机的设计方式发生了重大变化。直到世纪之交，性能上的进步是通过使一次可以执行一个程序的单个处理器速度更快实现的，通常是通过提高时钟信号的频率。但在世纪之交不久，事情变得很明显，这种方法遇到了障碍--更快的时钟意味着处理器变得更热，而硅芯片在失效之前可以散失的热量是有限的；这一限制正在迅速接近！突然之间，几个备受瞩目的项目被取消，该行业找到了一种提高性能的新方法。与其让一个处理器运行得更快，不如增加处理器核心的数量。多核处理器已经到来：首先是双核，然后是四核，以此类推。随着微芯片制造能力的不断提高，可集成到单个芯片上的晶体管数量不断增加，内核数量不断增加，现在多核系统正在让位于多核系统-具有10个内核的处理器，同时运行10个程序。这在硬件层面看起来很好-更多的晶体管意味着更多的内核-但这种从一个程序到多个程序同时运行的变化给为这些新系统开发应用程序的程序员带来了许多困难。编写一个在单个内核上运行的程序比编写一个实际上是同时运行的10个程序，以复杂和难以预测的方式相互作用的程序要好得多。为了让程序员的生活更加困难，对于多核系统，最好不要让所有的核都相同；相反，异类的多核系统提供了更高的效率，专门的核处理整个程序的特殊部分，但这对程序员来说更难管理。我们计划进行的项目计划将把计算机科学中最先进的技术引入这个复杂的问题，特别关注如何一起优化硬件和软件配置，以解决3D场景理解的重要应用领域。这将使未来安装了摄像头的智能手机能够扫描场景，不仅可以存储它看到的图片，还可以理解场景包括一所房子、一棵树和一辆移动的汽车。在解决这一应用的过程中，我们希望了解到许多关于优化也将具有更广泛适用性的多核系统的知识，以及使未来的电子产品更高效、更有能力和更有用的前景。

The last decade has seen a significant shift in the way computers are designed. Up to the turn of the millennium advances in performance were achieved by making a single processor, which could execute a single program at a time, go faster, usually by increasing the frequency of its clock signal. But shortly after the turn of the millennium it became clear that this approach was running into a brick wall - the faster clock meant the processor got hotter, and the amount of heat that can be dissipated in a silicon chip before it fails is limited; that limit was approaching rapidly!Quite suddenly several high-profile projects were cancelled and the industry found a new approach to higher performance. Instead of making one processor go ever faster, the number of processor cores could be increased. Multi-core processors had arrived: first dual core, then quad-core, and so on. As microchip manufacturing capability continues to increase the number of transistors that can be integrated on a single chip, the number of cores continues to rise, and now multi-core is giving way to many-core systems - processors with 10s of cores, running 10s of programs at the same time.This all seems fine at the hardware level - more transistors means more cores - but this change from one to many programs running at the same time has caused many difficulties for the programmers who develop applications for these new systems. Writing a program that runs on a single core is much better understood than writing a program that is actually 10s of programs running at the same time, interacting with each other in complex and hard-to-predict ways. To make life for the programmer even harder, with many-core systems it is often best not to make all the cores identical; instead, heterogeneous many-core systems offer the promise of much higher efficiency with specialised cores handling specialised parts of the overall program, but this is even harder for the programmer to manage.The Programme of projects we plan to undertake will bring the most advanced techniques in computer science to bear on this complex problem, focussing particularly on how we can optimise the hardware and software configurations together to address the important application domain of 3D scene understanding. This will enable a future smart phone fitted with a camera to scan a scene and not only to store the picture it sees, but also to understand that the scene includes a house, a tree, and a moving car. In the course of addressing this application we expect to learn a lot about optimising many-core systems that will have wider applicability too, and the prospect of making future electronic products more efficient, more capable, and more useful.