So I have a compute shader kernel with the following logic:
[numthreads(64,1,1)]
void CVProjectOX(uint3 t : SV_DispatchThreadID){
if(t.x >= TotalN)
return;
uint compt = DbMap[t.x];
....
I do understand that it's not ideal to have ifs elses/branching in compute shaders? if so, what is the best way to limit thread work if number of total expected threads aren't expected to match exactly the kernel's numthreads?
For instance in my example, the kernel group of 64 threads, let's say I expect total 961 threads (it could be anything really), if, I dispatch 960, 1 db slot won't be processed, if I dispatch 1024, there will be 63 unnecessary work or maybe work pointing to non-existing db slot. (db slots number will vary).
Is if(t.x > TotalN)/return fine and the right approach here?
Should I just do min, tx = min(t.x, TotalN) and keep writing on the final db slot?
Should I just modulo? tx = t.x % TotalN and rewrite the first db slots?
What other solutions?
Limiting the number of threads this way is fine, yes. But, be aware that an early return like this doesn't actually save (as much) work as you'd expect:
The hardware utilizes SIMD like thread collections (called wavefonts in directX). Depending on the hardware, the usual size of such a wavefont is usually 4 (Intel iGPUs), 32 (NVidia and most AMD GPUs) or 64 (a few AMD GPUs). Due to the nature of SIMD, all threads in such a wavefont always do exactly the same work, you can only "mask out" some of them (meaning, their writes will be ignored and they are fine reading out-of-bounds memory).
This means that, in the worst case (when the wavefont size is 64), when you need to execute 961 threads and are therefore dispatching 1024, there will still be 63 threads executing the code, they just behave like they wouldn't exist. If the wave size is smaller, the hardware might at least early out on some wavefonts, so in these cases the early return does actually save some work.
So it would be the best if you'd never actually need a number of threads that is not a multiple of your group size (which, in turn, is hopefully a multiple of the hardwares wavefont size). But, if that's not possible, limiting the number of threads in that way is the next best option, especially because all threads that do reach the early return are next to each other, which maximizes the chance that a whole wavefont can early out.
I am reading sensor output as square wave(0-5 volt) via oscilloscope. Now I want to measure frequency of one period with Beaglebone. So I should measure the time between two rising edges. However, I don't have any experience with working Beaglebone. Can you give some advices or sample codes about measuring time between rising edges?
How deterministic do you need this to be? If you can tolerate some inaccuracy, you can probably do it on the main Linux OS; if you want to be fancy pants, this seems like a potential use case for the BBB's PRU's (which I unfortunately haven't used so take this with substantial amounts of salt). I would expect you'd be able to write PRU code that just sits with an infinite outerloop and then inside that loop, start looping until it sees the pin shows 0, then starts looping until the pin shows 1 (this is the first rising edge), then starts counting until either the pin shows 0 again (this would then be the falling edge) or another loop to the next rising edge... either way, you could take the counter value and you should be able to directly convert that into time (the PRU is states as having fixed frequency for each instruction, and is a 200Mhz (50ns/instruction). Assuming your loop is something like
#starting with pin low
inner loop 1:
registerX = loadPin
increment counter
jump if zero registerX to inner loop 1
# pin is now high
inner loop 2:
registerX = loadPin
increment counter
jump if one registerX to inner loop 2
# pin is now low again
That should take 3 instructions per counter increment, so you can get the time as 3 * counter * 50 ns.
As suggested by Foon in his answer, the PRUs are a good fit for this task (although depending on your requirements it may be fine to use the ARM processor and standard GPIO). Please note that (as far as I know) both the regular GPIOs and the PRU inputs are based on 3.3V logic, and connecting a 5V signal might fry your board! You will need an additional component or circuit to convert from 5V to 3.3V.
I've written a basic example that measures timing between rising edges on the header pin P8.15 for my own purpose of measuring an engine's rpm. If you decide to use it, you should check the timing results against a known reference. It's about right but I haven't checked it carefully at all. It is implemented using PRU assembly and uses the pypruss python module to simplify interfacing.
I am doing a firmware upgrade using SPI bus on EEPROM as well as Internal ROM of 8051, basically writing a .hex file on both these memory devices.I am able to see .hex file written there.I am able to see slave and master are communicating properly, but not able to write anything on my memory devices.
If you have suggestions and if you have faced similar problems, please let me know where is the actual problem.
Any inputs would be welcomed.
Regards,
Ravi
I think more information will likely be required. In any case, here a few pitfalls I could see:
Hex Files are not necessarily memory images. The 8051s I've worked with usually use Intel Hex which is an ASCII format that describes the memory. The format is well documented here.
If you're having trouble writing to the EEPROM, you may not be writing the proper instructions. Typically, SPI EEPROM will be Byte addressed, but still has paging internally. You should start your writes on a Page boundary and write the whole page, then issue another write command, etc. By convention if you overrun a page, or start in the middle of a page it will loop around. So if your page is 8 bytes long, and you start writing 0-7 starting at index 4, you'll get:
Page Start: Index 0 = 4
Index 1 = 5
Index 2 = 6
Index 3 = 7
Index 4 = 0
Index 5 = 1
Index 6 = 2
Index 7 = 3
Most EEPROMs have locking mechanisms to prevent accidental writes once they are finalized. If the lock has been set, you will need to write an unlocking method (this will be detailed in the data sheet if it has it)
To further help you, please reference part numbers and better yet Data Sheets if you can.
I'm currently working on a project that involves a lot of bit level manipulation of data such as comparison, masking and shifting. Essentially I need to search through chunks of bitstreams between 8kbytes - 32kbytes long for bit patterns between 20 - 40bytes long.
Does anyone know of general resources for optimizing for such operations in CUDA?
There has been a least a couple of questions on SO on how to do text searches with CUDA. That is, finding instances of short byte-strings in long byte-strings. That is similar to what you want to do. That is, a byte-string search is much like a bit-string search where the number of bits in the byte-string can only be a multiple of 8, and the algorithm only checks for matches every 8 bits. Search on SO for CUDA string searching or matching, and see if you can find them.
I don't know of any general resources for this, but I would try something like this:
Start by preparing 8 versions of each of the search bit-strings. Each bit-string shifted a different number of bits. Also prepare start and end masks:
start
01111111
00111111
...
00000001
end
10000000
11000000
...
11111110
Then, essentially, perform byte-string searches with the different bit-strings and masks.
If you're using a device with compute capability >= 2.0, store the shifted bit-strings in global memory. The start and end masks can probably just be constants in your program.
Then, for each byte position, launch 8 threads that each checks a different version of the 8 shifted bit-strings against the long bit-string (which you now treat like a byte-string). In each block, launch enough threads to check, for instance, 32 bytes, so that the total number of threads per block becomes 32 * 8 = 256. The L1 cache should be able to hold the shifted bit-strings for each block, so that you get good performance.
I'm not talking about algorithmic stuff (eg use quicksort instead of bubblesort), and I'm not talking about simple things like loop unrolling.
I'm talking about the hardcore stuff. Like Tiny Teensy ELF, The Story of Mel; practically everything in the demoscene, and so on.
I once wrote a brute force RC5 key search that processed two keys at a time, the first key used the integer pipeline, the second key used the SSE pipelines and the two were interleaved at the instruction level. This was then coupled with a supervisor program that ran an instance of the code on each core in the system. In total, the code ran about 25 times faster than a naive C version.
In one (here unnamed) video game engine I worked with, they had rewritten the model-export tool (the thing that turns a Maya mesh into something the game loads) so that instead of just emitting data, it would actually emit the exact stream of microinstructions that would be necessary to render that particular model. It used a genetic algorithm to find the one that would run in the minimum number of cycles. That is to say, the data format for a given model was actually a perfectly-optimized subroutine for rendering just that model. So, drawing a mesh to the screen meant loading it into memory and branching into it.
(This wasn't for a PC, but for a console that had a vector unit separate and parallel to the CPU.)
In the early days of DOS when we used floppy discs for all data transport there were viruses as well. One common way for viruses to infect different computers was to copy a virus bootloader into the bootsector of an inserted floppydisc. When the user inserted the floppydisc into another computer and rebooted without remembering to remove the floppy, the virus was run and infected the harddrive bootsector, thus permanently infecting the host PC. A particulary annoying virus I was infected by was called "Form", to battle this I wrote a custom floppy bootsector that had the following features:
Validate the bootsector of the host harddrive and make sure it was not infected.
Validate the floppy bootsector and
make sure that it was not infected.
Code to remove the virus from the
harddrive if it was infected.
Code to duplicate the antivirus
bootsector to another floppy if a
special key was pressed.
Code to boot the harddrive if all was
well, and no infections was found.
This was done in the program space of a bootsector, about 440 bytes :)
The biggest problem for my mates was the very cryptic messages displayed because I needed all the space for code. It was like "FFVD RM?", which meant "FindForm Virus Detected, Remove?"
I was quite happy with that piece of code. The optimization was program size, not speed. Two quite different optimizations in assembly.
My favorite is the floating point inverse square root via integer operations. This is a cool little hack on how floating point values are stored and can execute faster (even doing a 1/result is faster than the stock-standard square root function) or produce more accurate results than the standard methods.
In c/c++ the code is: (sourced from Wikipedia)
float InvSqrt (float x)
{
float xhalf = 0.5f*x;
int i = *(int*)&x;
i = 0x5f3759df - (i>>1); // Now this is what you call a real magic number
x = *(float*)&i;
x = x*(1.5f - xhalf*x*x);
return x;
}
A Very Biological Optimisation
Quick background: Triplets of DNA nucleotides (A, C, G and T) encode amino acids, which are joined into proteins, which are what make up most of most living things.
Ordinarily, each different protein requires a separate sequence of DNA triplets (its "gene") to encode its amino acids -- so e.g. 3 proteins of lengths 30, 40, and 50 would require 90 + 120 + 150 = 360 nucleotides in total. However, in viruses, space is at a premium -- so some viruses overlap the DNA sequences for different genes, using the fact that there are 6 possible "reading frames" to use for DNA-to-protein translation (namely starting from a position that is divisible by 3; from a position that divides 3 with remainder 1; or from a position that divides 3 with remainder 2; and the same again, but reading the sequence in reverse.)
For comparison: Try writing an x86 assembly language program where the 300-byte function doFoo() begins at offset 0x1000... and another 200-byte function doBar() starts at offset 0x1001! (I propose a name for this competition: Are you smarter than Hepatitis B?)
That's hardcore space optimisation!
UPDATE: Links to further info:
Reading Frames on Wikipedia suggests Hepatitis B and "Barley Yellow Dwarf" virus (a plant virus) both overlap reading frames.
Hepatitis B genome info on Wikipedia. Seems that different reading-frame subunits produce different variations of a surface protein.
Or you could google for "overlapping reading frames"
Seems this can even happen in mammals! Extensively overlapping reading frames in a second mammalian gene is a 2001 scientific paper by Marilyn Kozak that talks about a "second" gene in rat with "extensive overlapping reading frames". (This is quite surprising as mammals have a genome structure that provides ample room for separate genes for separate proteins.) Haven't read beyond the abstract myself.
I wrote a tile-based game engine for the Apple IIgs in 65816 assembly language a few years ago. This was a fairly slow machine and programming "on the metal" is a virtual requirement for coaxing out acceptable performance.
In order to quickly update the graphics screen one has to map the stack to the screen in order to use some special instructions that allow one to update 4 screen pixels in only 5 machine cycles. This is nothing particularly fantastic and is described in detail in IIgs Tech Note #70. The hard-core bit was how I had to organize the code to make it flexible enough to be a general-purpose library while still maintaining maximum speed.
I decomposed the graphics screen into scan lines and created a 246 byte code buffer to insert the specialized 65816 opcodes. The 246 bytes are needed because each scan line of the graphics screen is 80 words wide and 1 additional word is required on each end for smooth scrolling. The Push Effective Address (PEA) instruction takes up 3 bytes, so 3 * (80 + 1 + 1) = 246 bytes.
The graphics screen is rendered by jumping to an address within the 246 byte code buffer that corresponds to the right edge of the screen and patching in a BRanch Always (BRA) instruction into the code at the word immediately following the left-most word. The BRA instruction takes a signed 8-bit offset as its argument, so it just barely has the range to jump out of the code buffer.
Even this isn't too terribly difficult, but the real hard-core optimization comes in here. My graphics engine actually supported two independent background layers and animated tiles by using different 3-byte code sequences depending on the mode:
Background 1 uses a Push Effective Address (PEA) instruction
Background 2 uses a Load Indirect Indexed (LDA ($00),y) instruction followed by a push (PHA)
Animated tiles use a Load Direct Page Indexed (LDA $00,x) instruction followed by a push (PHA)
The critical restriction is that both of the 65816 registers (X and Y) are used to reference data and cannot be modified. Further the direct page register (D) is set based on the origin of the second background and cannot be changed; the data bank register is set to the data bank that holds pixel data for the second background and cannot be changed; the stack pointer (S) is mapped to graphics screen, so there is no possibility of jumping to a subroutine and returning.
Given these restrictions, I had the need to quickly handle cases where a word that is about to be pushed onto the stack is mixed, i.e. half comes from Background 1 and half from Background 2. My solution was to trade memory for speed. Because all of the normal registers were in use, I only had the Program Counter (PC) register to work with. My solution was the following:
Define a code fragment to do the blend in the same 64K program bank as the code buffer
Create a copy of this code for each of the 82 words
There is a 1-1 correspondence, so the return from the code fragment can be a hard-coded address
Done! We have a hard-coded subroutine that does not affect the CPU registers.
Here is the actual code fragments
code_buff: PEA $0000 ; rightmost word (16-bits = 4 pixels)
PEA $0000 ; background 1
PEA $0000 ; background 1
PEA $0000 ; background 1
LDA (72),y ; background 2
PHA
LDA (70),y ; background 2
PHA
JMP word_68 ; mix the data
word_68_rtn: PEA $0000 ; more background 1
...
PEA $0000
BRA *+40 ; patched exit code
...
word_68: LDA (68),y ; load data for background 2
AND #$00FF ; mask
ORA #$AB00 ; blend with data from background 1
PHA
JMP word_68_rtn ; jump back
word_66: LDA (66),y
...
The end result was a near-optimal blitter that has minimal overhead and cranks out more than 15 frames per second at 320x200 on a 2.5 MHz CPU with a 1 MB/s memory bus.
Michael Abrash's "Zen of Assembly Language" had some nifty stuff, though I admit I don't recall specifics off the top of my head.
Actually it seems like everything Abrash wrote had some nifty optimization stuff in it.
The Stalin Scheme compiler is pretty crazy in that aspect.
I once saw a switch statement with a lot of empty cases, a comment at the head of the switch said something along the lines of:
Added case statements that are never hit because the compiler only turns the switch into a jump-table if there are more than N cases
I forget what N was. This was in the source code for Windows that was leaked in 2004.
I've gone to the Intel (or AMD) architecture references to see what instructions there are. movsx - move with sign extension is awesome for moving little signed values into big spaces, for example, in one instruction.
Likewise, if you know you only use 16-bit values, but you can access all of EAX, EBX, ECX, EDX , etc- then you have 8 very fast locations for values - just rotate the registers by 16 bits to access the other values.
The EFF DES cracker, which used custom-built hardware to generate candidate keys (the hardware they made could prove a key isn't the solution, but could not prove a key was the solution) which were then tested with a more conventional code.
The FSG 2.0 packer made by a Polish team, specifically made for packing executables made with assembly. If packing assembly isn't impressive enough (what's supposed to be almost as low as possible) the loader it comes with is 158 bytes and fully functional. If you try packing any assembly made .exe with something like UPX, it will throw a NotCompressableException at you ;)