Evaluation and Hardware Implementation of Real-Time Color Compression Algorithms

A major bottleneck, for performance as well as power consumption, for graphics hardware in mobile devices is the amount of data that needs to be transferred to and from memory. In, for example, hardware accelerated 3D graphics, a large part of the memory accesses are due to large and frequent color buffer data transfers. In a graphic hardware block color data is typically processed using RGB color format. For both 3D graphic rasterization and image composition several pixels needs to be read from and written to memory to generate a pixel in the frame buffer. This generates a lot of data traffic on the memory interfaces which impacts both performance and power consumption. Therefore it is important to minimize the amount of color buffer data. One way of reducing the memory bandwidth required is to compress the color data before writing it to memory and decompress it before using it in the graphics hardware block. This compression/decompression must be done “on-the-fly”, i.e. it has to be very fast so that the hardware accelerator does not have to wait for data. In this thesis, we investigated several exact (lossless) color compression algorithms from hardware implementation point of view to be used in high throughput hardware. Our study shows that compression/decompression datapath is well implementable even with stringent area and throughput constraints. However memory interfacing of these blocks is more critical and could be dominating