gpu上可变精度浮点缓冲区的无损压缩

Jeff Pool, A. Lastra, Montek Singh
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引用次数: 16

摘要

在这项工作中,我们探索了图形硬件上32位浮点缓冲区的无损压缩。我们首先采用了最先进的16位浮点颜色和深度缓冲压缩方案来操作32位数据,并提出了两个特定的增强功能:动态桶选择和斐波那契编码器。接下来,我们描述一个统一的编解码器,适用于任何类型的浮点缓冲区:颜色、深度、几何和GPGPU数据。我们还提出了一种进一步压缩变精度数据的方法。最后,我们在现有应用程序的颜色、深度和几何缓冲上测试我们的技术。通过对现有技术的改进,我们平均节省了1.26倍的带宽。我们的统一编解码器实现了1.5倍、7.9倍和2.9倍的平均带宽节省,用于颜色(包括过去工作不可压缩的缓冲区)、深度和几何缓冲区。当与我们的可变精度技术相结合时,甚至可以实现更高的节省,尽管具体的比例取决于应用程序对降低其精度的容忍度。
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Lossless compression of variable-precision floating-point buffers on GPUs
In this work, we explore the lossless compression of 32-bit floating-point buffers on graphics hardware. We first adapt a state-of-the-art 16-bit floating-point color and depth buffer compression scheme for operation on 32-bit data and propose two specific enhancements: dynamic bucket selection and a Fibonacci encoder. Next, we describe a unified codec for any type of floating-point buffer: color, depth, geometry, and GPGPU data. We also propose a method to further compress variable-precision data. Finally, we test our techniques on color, depth, and geometry buffers from existing applications. Using our enhancements to an existing technique, we have improved bandwidth savings by an average of 1.26x. Our unified codec achieved average bandwidth savings of 1.5x, 7.9x, and 2.9x for color (including buffers incompressible by past work), depth, and geometry buffers. Even higher savings were achieved when combined with our variable-precision technique, though specific ratios will depend on the tolerance of the application to reducing its precision.
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