Graphics for the Masses: A Hardware Rasterization Architecture for Mobile Phones

• The mobile phone is one of the most widespread devices with rendering capabilities. Those capabilities have been very limited because the resources on such devices are extremely scarce; small amounts of memory, little bandwidth, little chip area dedicated for special purposes, and limited power consumption. The small display resolutions present a further challenge; the angle subtended by a pixel is relatively large, and therefore reasonably high quality rendering is needed to generate high fidelity images.To increase the mobile rendering capabilities, we propose a new hardware architecture for rasterizing textured triangles. Our architecture focuses on saving memory bandwidth, since an external memory access typically is one of the most energy-consuming operations, and because mobile phones need to use as little power as possible. Therefore, our system includes three new key innovations: 1) an inexpensive multisampling scheme that gives relatively high quality at the same cost of previous inexpensive schemes, II) a texture minification system, including texture compression, which gives quality relatively close to trilinear mipmapping at the cost of 1.33 32-bit memory accesses on average, III) a scanline-based culling scheme that avoids a significant amount of z-buffer reads, and that only requires one context. Software simulations show that these three innovations together significantly reduce the memory bandwidth. and thus also the power consumption.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Engineering (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

graphics hardware

culling

multisampling

mobile phone

texture filtering

graphics hardware

texture filtering

mobile phone

culling

multisampling

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