What is the expected renderscript rsSample() performance? - performance

rsSample() seems intended for sampling from mipmapped textures across multiple levels of detail to avoid aliasing. The fisheye example would be a good use case.
The implementation simply samples 8 pixels from the underlying mipmap and does a linear blend of them.
It seems I can only get 15 Mpixels/second on a Google Pixel with this simple kernel:
uchar4 __attribute__((kernel)) rescaletest(uint32_t x, uint32_t y) {
float2 location = {x,y};
return convert_uchar4(rsSample(gInput8888, gWrapLinearMipLinear, location/2000.f, 1.5f)*255.f);
}
Considering all composited graphics presumably use mipmaps, and to composite even one texture at 60fps needs 120Mpixels/sec, what am I doing wrong?

Related

Optimizing texture fetches with higher mip levels

Let's say I have some shader program in DirectX or OpenGL rendering a full screen quad. And in a pixel/fragment shader I sample some huge textures at random texture coordinates. That is one same texture coordinate for all texture samplings in one shader invocation, but it is various among different shader invocations. These fetch operations produce performance drop, I even think that due to the size of the textures the GPU texture cache is not big enough and is used not efficiently.
Now I have a theoretical question: can I optimize the performance by using some low-resolution like 32x32 mask textures, which are built by mipmapping the large textures, and if a value in a mask texture at given texture coordinate at some higher mip level is not appropriate, then I don't need to perform texture fetches at full-size level 0? Something like this in HLSL (GLSL code is pretty similar, but there is no [branch] attribute):
float2 tc = calculateTexCoordinates();
bool performHeavyComputations = testValue(largeMipmappedTexture.SampleLevel(sampler, tc, 5));
float result = 0;
[branch]
if (performHeavyComputations)
{
result += largeMipmappedTexture.SampleLevel(sampler, tc, 0);
}
About 50% of texels at mip level 5 will not pass the test. And so a lot of shader invocations should not sample the full-size textures.
But I am introducing branching in the code. May this branching hurt the performance even worse than sampling the full-size texture even if that is not needed? Different GPUs may behave differently, some may not even support branching, will they perform two fetches instead of one?
I can test this code on some machines later, but my question is theoretical.
And can you suggest another optimizations, if this won't work properly ?

Summed area table in GLSL and GPU fragment shader execution

I am trying to compute the integral image (aka summed area table) of a texture I have in the GPU memory (a camera capture), the goal being to compute the adaptive threshold of said image. I'm using OpenGL ES 2.0, and still learning :).
I did a test with a simple gaussian blur shader (vertical/horizontal pass), which is working fine, but I need a way bigger variable average area for it to give satisfactory results.
I did implement a version of that algorithm on CPU before, but I'm a bit confused on how to implement that on a GPU.
I tried to do a (completely incorrect) test with just something like this for every fragment :
#version 100
#extension GL_OES_EGL_image_external : require
precision highp float;
uniform sampler2D u_Texture; // The input texture.
varying lowp vec2 v_TexCoordinate; // Interpolated texture coordinate per fragment.
uniform vec2 u_PixelDelta; // Pixel delta
void main()
{
// get neighboring pixels values
float center = texture2D(u_Texture, v_TexCoordinate).r;
float a = texture2D(u_Texture, v_TexCoordinate + vec2(u_PixelDelta.x * -1.0, 0.0)).r;
float b = texture2D(u_Texture, v_TexCoordinate + vec2(0.0, u_PixelDelta.y * 1.0)).r;
float c = texture2D(u_Texture, v_TexCoordinate + vec2(u_PixelDelta.x * -1.0, u_PixelDelta.y * 1.0)).r;
// compute value
float pixValue = center + a + b - c;
// Result stores value (R) and original gray value (G)
gl_FragColor = vec4(pixValue, center, center, 1.0);
}
And then another shader to get the area that I want and then get the average. This is obviously wrong as there's multiple execution units operating at the same time.
I know that the common way of computing a prefix sum on a GPU is to do it in two pass (vertical/horizontal, as discussed here on this thread or or here), but isn't there a problem here as there is a data dependency on each cell from the previous (top or left) one ?
I can't seem to understand the order in which the multiple execution units on a GPU will process the different fragments, and how a two-pass filter can solve that issue. As an example, if I have some values like this :
2 1 5
0 3 2
4 4 7
The two pass should give (first columns then rows):
2 1 5 2 3 8
2 4 7 -> 2 6 13
6 8 14 6 14 28
How can I be sure that, as an example, the value [0;2] will be computed as 6 (2 + 4) and not 4 (0 + 4, if the 0 hasn't been computed yet) ?
Also, as I understand that fragments are not pixels (If I'm not mistaken), would the values I store back in one of my texture in the first pass be the same in another pass if I use the exact same coordinates passed from the vertex shader, or will they be interpolated in some way ?
Tommy and Bartvbl address your questions about a summed-area table, but your core problem of an adaptive threshold may not need that.
As part of my open source GPUImage framework, I've done some experimentation with optimizing blurs over large radii using OpenGL ES. Generally, increasing blur radii leads to a significant increase in texture sampling and calculations per pixel, with an accompanying slowdown.
However, I found that for most blur operations you can apply a surprisingly effective optimization to cap the number of blur samples. If you downsample the image before blurring, blur at a smaller pixel radius (radius / downsampling factor), and then linearly upsample, you can arrive at a blurred image that is the equivalent of one blurred at a much larger pixel radius. In my tests, these downsampled, blurred, and then upsampled images look almost identical to the ones blurred based on the original image resolution. In fact, precision limits can lead to larger-radii blurs done at a native resolution breaking down in image quality past a certain size, where the downsampled ones maintain the proper image quality.
By adjusting the downsampling factor to keep the downsampled blur radius constant, you can achieve near constant-time blurring speeds in the face of increasing blur radii. For a adaptive threshold, the image quality should be good enough to use for your comparisons.
I use this approach in the Gaussian and box blurs within the latest version of the above-linked framework, so if you're running on Mac, iOS, or Linux, you can evaluate the results by trying out one of the sample applications. I have an adaptive threshold operation based on a box blur that uses this optimization, so you can see if the results there are what you want.
AS per the above, it's not going to be fantastic on a GPU. But assuming the cost of shunting data between the GPU and CPU is more troubling it may still be worth persevering.
The most obvious prima facie solution is to split horizontal/vertical as discussed. Use an additive blending mode, create a quad that draws the whole source image then e.g. for the horizontal step on a bitmap of width n issue a call that requests the quad be drawn n times, the 0th time at x = 0, the mth time at x = m. Then ping pong via an FBO, switching the target of buffer of the horizontal draw into the source texture for the vertical.
Memory accesses are probably O(n^2) (i.e. you'll probably cache quite well, but that's hardly a complete relief) so it's a fairly poor solution. You could improve it by divide and conquer by doing the same thing in bands — e.g. for the vertical step, independently sum individual rows of 8, after which the error in every row below the final is the failure to include whatever the sums are on that row. So perform a second pass to propagate those.
However an issue with accumulating in the frame buffer is clamping to avoid overflow — if you're expecting a value greater than 255 anywhere in the integral image then you're out of luck because the additive blending will clamp and GL_RG32I et al don't reach ES prior to 3.0.
The best solution I can think of to that, without using any vendor-specific extensions, is to split up the bits of your source image and combine channels after the fact. Supposing your source image were 4 bit and your image less than 256 pixels in both directions, you'd put one bit each in the R, G, B and A channels, perform the normal additive step, then run a quick recombine shader as value = A + (B*2) + (G*4) + (R*8). If your texture is larger or smaller in size or bit depth then scale up or down accordingly.
(platform specific observation: if you're on iOS then you've hopefully already got a CVOpenGLESTextureCache in the loop, which means you have CPU and GPU access to the same texture store, so you might well prefer to kick this step off to GCD. iOS is amongst the platforms supporting EXT_shader_framebuffer_fetch; if you have access to that then you can write any old blend function you like and at least ditch the combination step. Also you're guaranteed that preceding geometry has completed before you draw so if each strip writes its totals where it should and also to the line below then you can perform the ideal two-pixel-strips solution with no intermediate buffers or state changes)
What you attempt to do cannot be done in a fragment shader. GPU's are by nature very different to CPU's by executing their instructions in parallel, in massive numbers at the same time. Because of this, OpenGL does not make any guarantees about execution order, because the hardware physically doesn't allow it to.
So there is not really any defined order other than "whatever the GPU thread block scheduler decides".
Fragments are pixels, sorta-kinda. They are pixels that potentially end up on screen. If another triangle ends up in front of another, the previous calculated colour value is discarded. This happens regardless of whatever colour was stored at that pixel in the colour buffer previously.
As for creating the summed area table on the GPU, I think you may first want to look at GLSL "Compute Shaders", which are specifically made for this sort of thing.
I think you may be able to get this to work by creating a single thread for each row of pixels in the table, then have every thread "lag behind" by 1 pixel compared to the previous row.
In pseudocode:
int row_id = thread_id()
for column_index in (image.cols + image.rows):
int my_current_column_id = column_index - row_id
if my_current_column_id >= 0 and my_current_column_id < image.width:
// calculate sums
The catch of this method is that all threads should be guaranteed to execute their instructions simultaneously without getting ahead of one another. This is guaranteed in CUDA, but I'm not sure whether it is in OpenGL compute shaders. It may be a starting point for you, though.
It may look surprising for the beginner but the prefix sum or SAT calculation is suitable for parallelization. As the Hensley algorithm is the most intuitive to understand (also implemented in OpenGL), more work-efficient parallel methods are available, see CUDA scan. The paper from Sengupta discuss parallel method which seems state-of-the-art efficient method with reduce and down swap phases. These are valuable materials but they do not enter OpenGL shader implementations in detail. The closest document is the presentation you have found (it refers to Hensley publication), since it has some shader snippets. This is the job which is doable entirely in fragment shader with FBO Ping-Pong. Note that the FBO and its texture need to have internal format set to high precision - GL_RGB32F would be best but I am not sure if it is supported in OpenGL ES 2.0.

Is it better to use a single texture or multiple textures for a YUV image

This question is for OpenGL ES 2.0 (on Android) but may be more general to OpenGL.
Ultimately all performance questions are implementation-dependent, but if anyone can answer this question in general or based on their experience that would be helpful. I'm writing some test code as well.
I have a YUV (12bpp) image I'm loading into a texture and color-converting in my fragment shader. Everything works fine but I'd like to see where I can improve performance (in terms of frames per second).
Currently I'm actually loading three textures for each image - one for the Y component (of type GL_LUMINANCE), one for the U component (of type GL_LUMINANCE and of course 1/4 the size of the Y component), and one for the V component (of type GL_LUMINANCE and of course 1/4 the size of the Y component).
Assuming I can get the YUV pixels in any arrangement (e.g. the U and V in separate planes or interspersed), would it be better to consolidate the three textures into only two or only one? Obviously it's the same number of bytes to push to the GPU no matter how you do it, but maybe with fewer textures there would be less overhead. At the very least, it would use fewer texture units. My ideas:
If the U and V pixels were interspersed with each other, I could load them in a single texture of type GL_LUMINANCE_ALPHA which has two components.
I could load the entire YUV image as a single texture (of type GL_LUMINANCE but 3/2 the size of the image) and then in the fragment shader I could call texture2D() three times on the same texture, doing a bit of arithmetic figure out the correct co-ordinates to pass to texture2D to get the correct texture co-ordinates for the Y, U and V components.
I would combine the data into as few textures as possible. Fewer textures is usually a better option for a few reasons.
Fewer state changes to setup the draw call.
The fewer texture fetches in a fragment shader the better.
Less upload time.
Sources:
I understand some of these are focused on more specific hardware, but the principles apply to most Mobile graphics architectures.
Best Practices for Working with Texture Data
Optimize OpenGL for Tegra
Optimizing performance of a heavy fragment shader
"Binding to a texture takes time for OpenGL ES to process. Apps that reduce the number of changes they make to OpenGL ES state perform better. "
"In my experience mobile GPU performance is roughly proportional to the number of texture2D calls." "There are two texture loads, so the minimum cycle count for the texture sub-unit is two." (Tegra has a texture unit which has to run a cycle for reach texture read)
"making calls to the glTexSubImage and glCopyTexSubImage functions particularly expensive" - upload operations must stall the pipeline until textures are uploaded. It is faster to batch these into a single upload than block a bunch of separate times.

OpenGL - Fast Textured Quads?

I am trying to display as many textured quads as possible at random positions in the 3D space. In my experience so far, I cannot display even a couple of thousands of them without dropping the fps significantly under 30 (my camera movement script becomes laggy).
Right now I am following an ancient tutorial. After initializing OpenGL:
glEnable(GL_TEXTURE_2D);
glShadeModel(GL_SMOOTH);
glClearColor(0, 0, 0, 0);
glClearDepth(1.0f);
glEnable(GL_DEPTH_TEST);
glDepthFunc(GL_LEQUAL);
glHint(GL_PERSPECTIVE_CORRECTION_HINT, GL_NICEST);
I set the viewpoint and perspective:
glViewport(0,0,width,height);
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
gluPerspective(60.0f,(GLfloat)width/(GLfloat)height,0.1f,100.0f);
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
Then I load some textures:
glGenTextures(TEXTURE_COUNT, &texture[0]);
for (int i...){
glBindTexture(GL_TEXTURE_2D, texture[i]);
glTexParameteri(GL_TEXTURE_2D,GL_TEXTURE_MAG_FILTER,GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D,GL_TEXTURE_MIN_FILTER,GL_LINEAR_MIPMAP_NEAREST);
gluBuild2DMipmaps(GL_TEXTURE_2D,3,TextureImage[0]->w,TextureImage[0]->h,GL_RGB,GL_UNSIGNED_BYTE,TextureImage[0]->pixels);
}
And finally I draw my GL_QUADS using:
glBindTexture(GL_TEXTURE_2D, q);
glTranslatef(fDistanceX,fDistanceZ,-fDistanceY);
glBegin(GL_QUADS);
glNormal3f(a,b,c);
glTexCoord2f(d, e); glVertex3f(x1, y1, z1);
glTexCoord2f(f, g); glVertex3f(x2, y2, z2);
glTexCoord2f(h, k); glVertex3f(x3, y3, z3);
glTexCoord2f(m, n); glVertex3f(x4, y4, z4);
glEnd();
glTranslatef(-fDistanceX,-fDistanceZ,fDistanceY);
I find all that code very self explaining. Unfortunately that way to do things is deprecated, as far as I know. I read some vague things about PBO and vertexArrays on the internet, but i did not find any tutorial on how to use them. I don't even know if these objects are suited to realize what I am trying to do here (a billion quads on the screen without a lag). Perhaps anyone here could give me a definitive suggestion, of what I should use to achieve the result? And if you happen to have one more minute of spare time, could you give me a short summary of how these functions are used (just as i did with the deprecated ones above)?
Perhaps anyone here could give me a definitive suggestion, of what I should use to achieve the result?
What is "the result"? You have not explained very well what exactly it is that you're trying to accomplish. All you've said is that you're trying to draw a lot of textured quads. What are you trying to do with those textured quads?
For example, you seem to be creating the same texture, with the same width and height, given the same pixel data. But you store these in different texture objects. OpenGL does not know that they contain the same data. Therefore, you spend a lot of time swapping textures needlessly when you render quads.
If you're just randomly drawing them to test performance, then the question is meaningless. Such tests are pointless, because they are entirely artificial. They test only this artificial scenario where you're changing textures every time you render a quad.
Without knowing what you are trying to ultimately render, the only thing I can do is give general performance advice. In order (ie: do the first before you do the later ones):
Stop changing textures for every quad. You can package multiple images together in the same texture, then render all of the quads that use that texture at once, with only one glBindTexture call. The texture coordinates of the quad specifies which image within the texture that it uses.
Stop using glTranslate to position each individual quad. You can use it to position groups of quads, but you should do the math yourself to compute the quad's vertex positions. Once those glTranslate calls are gone, you can put multiple quads within the space of a single glBegin/glEnd pair.
Assuming that your quads are static (fixed position in model space), consider using a buffer object to store and render with your quad data.
I read some vague things about PBO and vertexArrays on the internet, but i did not find any tutorial on how to use them.
Did you try the OpenGL Wiki, which has a pretty good list of tutorials (as well as general information on OpenGL)? In the interest of full disclosure, I did write one of them.
I heard, in modern games milliards of polygons are rendered in real time
Actually its in the millions. I presume you're German: "Milliarde" translates into "Billion" in English.
Right now I am following an ancient tutorial.
This is your main problem. Contemporary OpenGL applications don't use ancient rendering methods. You're using the immediate mode, which means that you're going through several function calls to just submit a single vertex. This is highly inefficient. Modern applications, like games, can reach that high triangle counts because they don't waste their CPU time on calling as many functions, they don't waste CPU→GPU bandwidth with the data stream.
To reach that high counts of triangles being rendered in realtime you must place all the geometry data in the "fast memory", i.e. in the RAM on the graphics card. The technique OpenGL offers for this is called "Vertex Buffer Objects". Using a VBO you can draw large batches of geometry using a single drawing call (glDrawArrays, glDrawElements and their relatives).
After getting the geometry out of the way, you must be nice to the GPU. GPUs don't like it, if you switch textures or shaders often. Switching a texture invalidates the contents of the cache(s), switching a shader means stalling the GPU pipeline, but worse it means invalidating the execution path prediction statistics (the GPU takes statistics which execution paths of a shader are the most probable to be executed and which memory access patterns it exhibits, this used to iteratively optimize the shader execution).

How WebGL works?

I'm looking for deep understanding of how WebGL works. I'm wanting to gain knowledge at a level that most people care less about, because the knowledge isn't necessary useful to the average WebGL programmer. For instance, what role does each part(browser, graphics driver, etc..) of the total rendering system play in getting an image on the screen?
Does each browser have to create a javascript/html engine/environment in order to run WebGL in browser? Why is chrome a head of everyone else in terms of being WebGL compatible?
So, what's some good resources to get started? The kronos specification is kind of lacking( from what I saw browsing it for a few minutes ) for what I'm wanting. I'm wanting mostly how is this accomplished/implemented in browsers and what else needs to change on your system to make it possible.
Hopefully this little write-up is helpful to you. It overviews a big chunk of what I've learned about WebGL and 3D in general. BTW, if I've gotten anything wrong, somebody please correct me -- because I'm still learning, too!
Architecture
The browser is just that, a Web browser. All it does is expose the WebGL API (via JavaScript), which the programmer does everything else with.
As near as I can tell, the WebGL API is essentially just a set of (browser-supplied) JavaScript functions which wrap around the OpenGL ES specification. So if you know OpenGL ES, you can adopt WebGL pretty quickly. Don't confuse this with pure OpenGL, though. The "ES" is important.
The WebGL spec was intentionally left very low-level, leaving a lot to
be re-implemented from one application to the next. It is up to the
community to write frameworks for automation, and up to the developer
to choose which framework to use (if any). It's not entirely difficult
to roll your own, but it does mean a lot of overhead spent on
reinventing the wheel. (FWIW, I've been working on my own WebGL
framework called Jax for a while
now.)
The graphics driver supplies the implementation of OpenGL ES that actually runs your code. At this point, it's running on the machine hardware, below even the C code. While this is what makes WebGL possible in the first place, it's also a double edged sword because bugs in the OpenGL ES driver (which I've noted quite a number of already) will show up in your Web application, and you won't necessarily know it unless you can count on your user base to file coherent bug reports including OS, video hardware and driver versions. Here's what the debug process for such issues ends up looking like.
On Windows, there's an extra layer which exists between the WebGL API and the hardware: ANGLE, or "Almost Native Graphics Layer Engine". Because the OpenGL ES drivers on Windows generally suck, ANGLE receives those calls and translates them into DirectX 9 calls instead.
Drawing in 3D
Now that you know how the pieces come together, let's look at a lower level explanation of how everything comes together to produce a 3D image.
JavaScript
First, the JavaScript code gets a 3D context from an HTML5 canvas element. Then it registers a set of shaders, which are written in GLSL ([Open] GL Shading Language) and essentially resemble C code.
The rest of the process is very modular. You need to get vertex data and any other information you intend to use (such as vertex colors, texture coordinates, and so forth) down to the graphics pipeline using uniforms and attributes which are defined in the shader, but the exact layout and naming of this information is very much up to the developer.
JavaScript sets up the initial data structures and sends them to the WebGL API, which sends them to either ANGLE or OpenGL ES, which ultimately sends it off to the graphics hardware.
Vertex Shaders
Once the information is available to the shader, the shader must transform the information in 2 phases to produce 3D objects. The first phase is the vertex shader, which sets up the mesh coordinates. (This stage runs entirely on the video card, below all of the APIs discussed above.) Most usually, the process performed on the vertex shader looks something like this:
gl_Position = PROJECTION_MATRIX * VIEW_MATRIX * MODEL_MATRIX * VERTEX_POSITION
where VERTEX_POSITION is a 4D vector (x, y, z, and w which is usually set to 1); VIEW_MATRIX is a 4x4 matrix representing the camera's view into the world; MODEL_MATRIX is a 4x4 matrix which transforms object-space coordinates (that is, coords local to the object before rotation or translation have been applied) into world-space coordinates; and PROJECTION_MATRIX which represents the camera's lens.
Most often, the VIEW_MATRIX and MODEL_MATRIX are precomputed and
called MODELVIEW_MATRIX. Occasionally, all 3 are precomputed into
MODELVIEW_PROJECTION_MATRIX or just MVP. These are generally meant
as optimizations, though I'd like find time to do some benchmarks. It's
possible that precomputing is actually slower in JavaScript if it's
done every frame, because JavaScript itself isn't all that fast. In
this case, the hardware acceleration afforded by doing the math on the
GPU might well be faster than doing it on the CPU in JavaScript. We can
of course hope that future JS implementations will resolve this potential
gotcha by simply being faster.
Clip Coordinates
When all of these have been applied, the gl_Position variable will have a set of XYZ coordinates ranging within [-1, 1], and a W component. These are called clip coordinates.
It's worth noting that clip coordinates is the only thing the vertex shader really
needs to produce. You can completely skip the matrix transformations
performed above, as long as you produce a clip coordinate result. (I have even
experimented with swapping out matrices for quaternions; it worked
just fine but I scrapped the project because I didn't get the
performance improvements I'd hoped for.)
After you supply clip coordinates to gl_Position WebGL divides the result by gl_Position.w producing what's called normalized device coordinates.
From there, projecting a pixel onto the screen is a simple matter of multiplying by 1/2 the screen dimensions and then adding 1/2 the screen dimensions.[1] Here are some examples of clip coordinates translated into 2D coordinates on an 800x600 display:
clip = [0, 0]
x = (0 * 800/2) + 800/2 = 400
y = (0 * 600/2) + 600/2 = 300
clip = [0.5, 0.5]
x = (0.5 * 800/2) + 800/2 = 200 + 400 = 600
y = (0.5 * 600/2) + 600/2 = 150 + 300 = 450
clip = [-0.5, -0.25]
x = (-0.5 * 800/2) + 800/2 = -200 + 400 = 200
y = (-0.25 * 600/2) + 600/2 = -150 + 300 = 150
Pixel Shaders
Once it's been determined where a pixel should be drawn, the pixel is handed off to the pixel shader, which chooses the actual color the pixel will be. This can be done in a myriad of ways, ranging from simply hard-coding a specific color to texture lookups to more advanced normal and parallax mapping (which are essentially ways of "cheating" texture lookups to produce different effects).
Depth and the Depth Buffer
Now, so far we've ignored the Z component of the clip coordinates. Here's how that works out. When we multiplied by the projection matrix, the third clip component resulted in some number. If that number is greater than 1.0 or less than -1.0, then the number is beyond the view range of the projection matrix, corresponding to the matrix zFar and zNear values, respectively.
So if it's not in the range [-1, 1] then it's clipped entirely. If it is in that range, then the Z value is scaled to 0 to 1[2] and is compared to the depth buffer[3]. The depth buffer is equal to the screen dimensions, so that if a projection of 800x600 is used, the depth buffer is 800 pixels wide and 600 pixels high. We already have the pixel's X and Y coordinates, so they are plugged into the depth buffer to get the currently stored Z value. If the Z value is greater than the new Z value, then the new Z value is closer than whatever was previously drawn, and replaces it[4]. At this point it's safe to light up the pixel in question (or in the case of WebGL, draw the pixel to the canvas), and store the Z value as the new depth value.
If the Z value is greater than the stored depth value, then it is deemed to be "behind" whatever has already been drawn, and the pixel is discarded.
[1]The actual conversion uses the gl.viewport settings to convert from normalized device coordinates to pixels.
[2]It's actually scaled to the gl.depthRange settings. They default 0 to 1.
[3]Assuming you have a depth buffer and you've turned on depth testing with gl.enable(gl.DEPTH_TEST).
[4]You can set how Z values are compared with gl.depthFunc
I would read these articles
http://webglfundamentals.org/webgl/lessons/webgl-how-it-works.html
Assuming those articles are helpful, the rest of the picture is that WebGL runs in a browser. It renderers to a canvas tag. You can think of a canvas tag like an img tag except you use the WebGL API to generate an image instead of download one.
Like other HTML5 tags the canvas tag can be styled with CSS, be under or over other parts of the page. Is composited (blended) with other parts of the page. Be transformed, rotated, scaled by CSS along with other parts of the page. That's a big difference from OpenGL or OpenGL ES.

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