支持 CUDA 和 OpenCL，Indigo Renderer CPU+GPU 渲染器

Edison

http://www.indigorenderer.com/node/1012

Graphics processing units (GPUs) have come a long way since their inception, when they were used to accelerate basic rasterisation features in high-end CAD workstations. Through standards such as 3Dfx's Glide, and later Direct3D and OpenGL, the market for inexpensive consumer GPUs has bloomed into the success story it is today.

Together with phenomenal performance increases, we have benefitted from increased programmability through new standards such as CUDA and OpenCL. It is these improvements that have allowed us to reach the stage where GPUs can be used to accelerate general purpose computations. Rendering naturally benefits from both the specialised graphics functionality and the general purpose computational power found in GPUs, and so one could say it is only a matter of time before these additional resources are exploited by all rendering software.

Today we are proud to announce GPU acceleration support for Indigo Renderer.

After considerable development effort in which we evaluated both CUDA and OpenCL platforms, we are ready to present preliminary results and ask users to join our GPU acceleration beta testing group. Both ATI and NVIDIA users are welcome to participate!

If you are interested in joining the beta group, please email us at contact@indigorenderer.com.

About the technology

We are employing a hybrid CPU+GPU approach, whereby we offload some of the CPU's computations onto the GPU. This has a number of benefits, the foremost of which being that we support the long list of features that make Indigo the powerful rendering engine it is.

Motion blur:

GPU-accelerated unbiased motion blur. Images rendered in 3 minutes. Click for high-res image.

Instancing:

50,000 instances and 54 billion triangles. Brute force SSS with Buddhas! Click for high-res image.

It's fast:

Image rendered in 2 minutes. Model by Ronen Bekerman. Click for high-res image.

We have also improved our path tracing code to be more intelligent and efficient, meaning that the time to produce a clean image is greatly reduced compared to other path tracers, including Indigo 2.2.

With the core functionality in place and promising first results, we will be spending time to optimise our CPU-based code to deliver awe-inspiring performance in the CPU+GPU combo; we expect more large performance increases in the near term.

luckissy

他们用来加速中高端 CAD 工作站 rasterisation 基本功能时，图形 pro cessing 单元 (gpu) 有自其成立以来，取得长足进展。 通过如 3Dfx 的氨 ide，和更高版本 Direct3D 和 OpenGL 的标准为廉价消费 gpu 市场已绽放到今天的成功故事。

连同非凡性能的增加我们受惠增加可编程性通过新的标准如 CUDA 和 OpenCL。 它是这些使我们台阶 gpu，可用于加速通用计算的改进。 呈现自然从专门的图形功能和一般用途的效益计算的 gpu，发现电源，因此可以说它之前这些额外的资源，可以利用所有的时间只呈现软件。

今天我们非常自豪地宣布对靛蓝输出程序 GPU 加速支持。

之后取得的显著发展努力，在其中我们求值 CUDA 和 OpenCL 的平台，我们准备展示初步结果，请加入我们 GPU 加速测试组的用户。 NVIDIA 和 ATI 的用户，欢迎参与 ！

如果您有兴趣参加测试组请给我们发电子邮件至 contact@indigorenderer.com 在。

相关技术
我们采用的混合型的 CPU + GPU 方法，使我们卸载某些 CPU 的计算到 GPU 上。 这有很多好处，其中，我们支持功能，可使靛蓝的长列表功能强大的呈现引擎它最重要的是。

运动模糊：

GPU 加速的无偏的运动模糊。 在 3 分钟内呈现的图像。 单击此处可高分辨率图像。

实例化：

54 亿元三角形和 50000 实例。 暴力与佛 SSS ！ 单击此处可高分辨率图像。

它是快速：

在 2 分钟内呈现的图像。 模型的 Ronen Bekerman。 单击此处可高分辨率图像。

我们还提高了我们要更多 英特尔 ligent 的路径跟踪代码和比作其他路径示踪剂，包括靛蓝 2.2 的高效率） 文件名意味着以产生一个干净的映像的时间大大减少。

在地方和有希望的第一个成果的核心功能我们将会动用时间来优化我们基于 CPU 的代码提供 CPU + GPU 组合威严的性能 ； 我们期望在短期内更多大型的性能提高。

Bing

gz_easy

50,000 instances and 54 billion triangles，这要多少时间才能渲染一帧。

Edison

唔，唯独这个没有渲染时间提供

河蟹万岁

luxrender opencl
bunkspeed shot cuda

carterczr

支持3Ds Max吗？