Understanding why some e-Readers fall short of performing as Android tablets (Setting, Hidden Benefits).

There is a fact about modern graphics chips which some people may not be aware of – especially some Linux users – but which I was recently reminded of because I have bought an e-Reader that has the Android O/S, but that features the energy-saving benefits of “e-Ink” – an innovative technology that has a surface somewhat resembling paper, the brightness of which can vary between white and black, but that mainly uses available light, although back-lit and front-lit versions of e-Ink now exist, and that consumes very little current, so that it’s frequently possible to read an entire book on one battery-charge. With an average Android tablet that merely has an LCD, the battery-life can impede enjoying an e-Book.

An LCD still has in common with the old CRTs, being refreshed at a fixed frequency by something called a “raster” – a pattern that scans a region of memory and feeds pixel-values to the display sequentially, but maybe 60 times per second, thus refreshing the display that often. e-Ink pixels are sent a signal once, to change brightness, and then stay at the assigned brightness level until they receive another signal, to change again. What this means is that, at the hardware-level, e-Ink is less powerful than ‘frame-buffer devices’ once were.

But any PC, Mac or Android graphics card or graphics chip manufactured later than in the 1990s has a non-trivial GPU – a ‘Graphics Processing Unit’ – that acts as a co-processor, working in parallel with the computer’s main CPU, to take much of the workload off the CPU, associated with rendering graphics to the screen. Much of what a modern GPU does consists of taking as input, pixels which software running on the CPU wrote either to a region of dedicated graphics memory, or, in the case of an Android device, to a region of memory shared between the GPU and the CPU, but part of the device’s RAM. And the GPU then typically ‘transforms’ the image of these pixels, to the way they will appear on the screen, finally. This ends up modifying a ‘Frame-Buffer’, the contents of which are controlled by the GPU and not the CPU, but which the raster scans, resulting in output to the actual screen.

Transforming an image can take place in a strictly 2D sense, or can take place in a sense that preserves 3D perspective, but that results in 2D screen-output. And it gets applied to desktop graphics as much as to application content. In the case of desktop graphics, the result is called ‘Compositing’, while in the case of application content, the result is either fancier output, or faster execution of the application, on the CPU. And on many Android devices, compositing results in multiple Home-Screens that can be scrolled, and the glitz of which is proven by how smoothly they scroll.

Either way, a modern GPU is much more versatile than a frame-buffer device was. And its benefits can contribute in unexpected places, such as when an application outputs text to the screen, but when the text is merely expected to scroll. Typically, the rasterization of fonts still takes place on the CPU, but results in pixel-values being written to shared memory, that correspond to text to be displayed. But the actual scrolling of the text can be performed by the GPU, where more than one page of text, with a fixed position in the drawing surface the CPU drew it to, is transformed by the GPU to advancing screen-positions, without the CPU having to redraw any pixels. (:1) This effect is often made more convincing, by the fact that at the end of a sequence, a transformed image is sometimes replaced by a fixed image, in a transition of the output, but between two graphics that are completely identical. These two graphics would reside in separate regions of RAM, even though the GPU can render a transition between them.

(Updated 4/20/2019, 12h45 … )

Continue reading Understanding why some e-Readers fall short of performing as Android tablets (Setting, Hidden Benefits).

“Hardware Acceleration” is a bit of a Misnomer.

The term gets mentioned quite frequently, that certain applications offer to give the user services, with “Hardware Acceleration”. This terminology can in fact be misleading – in a way that has no consequences – because computations that are hardware-accelerated, are still being executed according to software that has either been compiled or assembled into micro-instructions. Only, those micro-instructions are not to be executed on the main CPU of the machine.

Instead, those micro-instructions are to be executed either on the GPU, or on some other coprocessor, which provide the accelerating hardware.

Often, the compiling of code meant to run on a GPU – even though the same, in theory as regular software – has its own special considerations. For example, this code often consists of only a few micro-instructions, over which great care must be taken to make sure that they run correctly on as many GPUs as possible. I.e., when we are coding a shader, KISS is often a main paradigm. And the possibility crops up often in practice, that even though the code is technically correct, it does not run correctly on a given GPU.

I do not really know how it is with SIMD coprocessors.

But this knowledge would be useful to have, in order to understand this posting of mine.

Of course, there exists a major contradiction to what I just wrote, in OpenCL and CUDA.

Continue reading “Hardware Acceleration” is a bit of a Misnomer.