What is the smallest audio buffer needed to produce Tone sound without distotions with WaveOUT API - audio

Does the WaveOut API has some internal limitation of the size for the current piece of buffer played ? I mean if I provide a very small buffer does it affects somehow the sound played to the speakers. I am experiencing very strange noise when I am generating and playing the sinus wave with small buffer. Something like a peak, or "BUMP".
The complete Story:
I made a program that can generate Sinus sound signal in real time.
The variable parameters are Frequency and Volume. The project requirement was to have a maximum latency of 50 ms. So the program must be able to produce Sinus signals with manually adjustable frequency of audio signal in real time.
I used Windows WaveOut API, C# and P/invoke to access the API.
Everything works fine when the sound buffer is 1000 ms large. If I minimize the buffer to 50 ms as per latency requirement then for certain frequencies I am experiencing at the end of every buffer, a noise or "BUMP". I do not understand if the sound generated is malformed ( I checked and is not) or something happens with the Audio chip, or some delay in initializing and playing.
When I save the produced audio to .wav file everything is perfect.
This means the must be some bug in my code or the audio subsystem has a limitation to the buffer chunks sent to it.
For those who doesn't know WaveOut must be initialized at first time and then must be prepared with audio headers for each buffer that are containing the number of bytes that needs to be played and the pointer to a memory that contains the audio that needs to be player.
UPDATE
Noise happens with the following combinations 44100 SamplingRate, 16 Bits, 2 channels, 50 ms buffer and generated Sinus audio signal of 201Hz, 202Hz, 203Hz, 204Hz, 205Hz ... 219Hz,
220Hz, 240 Hz, is ok
Why is this difference of 20, I do not know.

There are a few things to keep in mind when you need to output audio smoothly:
waveOutXxxx API is a legacy/compatibility layer on top of lower level API and as such it has greater overhead and is not recommended when you are to reach minimal latency. Note that this is unlikely to be your primary problem, but this is a piece of general knowledge helpful for understanding
because Windows is not real time OS and its audio subsystem is not realtime either you don't have control over random latency involved between you queue audio data for output and the data is really played back, the key is to keep certain level of buffer fullness which protects you from playback underflows and delivers smooth playback
with waveOutXxxx you are no limited to having single buffer, you can allocate multiple reusable buffers and recycle them
All in all, waveOutXxxx, DirectSound, DirectShow APIs work well with latencies 50 ms and up. With WASAPI exclusive mode streams you can get 5 ms latencies and even lower.
EDIT: I seem to have said too early about 20 ms latencies. To compensate for this, here is a simple tool LowLatencyWaveOutPlay (Win32, x64) to estimate the latency you can achieve. With sufficient buffering playback is smooth, otherwise you hear stuttering.
My understanding is that buffers might be returned late and the optimal design in terms of smallest latency lies along the line of having more smaller buffers so that you are given them back as early as possible. For example, 10 buffers 3 ms/buffer rather than 3 buffers 10 ms/buffer.
D:\>LowLatencyWaveOutPlay.exe 48000 10 3
Format: 48000 Hz, 1 channels, 16 bits per sample
Buffer Count: 10
Buffer Length: 3 ms (288 bytes)
Signal Frequency: 1000 Hz
^C

So I came here because I wanted to find the basic latency of waveoutwrite() as well. I got around 25-26ms of latency before I got to the smooth sine tone.
This is for:
AMD Phenom(tm) 9850 Quad-Core Processor 2.51 GHz
4.00 GB ram
64-bit operating system, x64-based processor
Windows 10 Enterprise N
The code follows. It is a modfied version of Petzold's sine wave program, refactored to run on the command line. I also changed the polling of buffers to use of a callback on buffer complete with the idea that this would make the program more efficient, but it didn't make a difference.
It also has a setup for elapsed timing, which I used to probe various timings for operations on the buffers. Using those I get:
Sine wave output program
Channels: 2
Sample rate: 44100
Bytes per second: 176400
Block align: 4
Bits per sample: 16
Time per buffer: 0.025850
Total time prepare header: 87.5000000000 usec
Total time to fill: 327.9000000000 usec
Total time for waveOutWrite: 90.8000000000 usec
Program:
/*******************************************************************************
WaveOut example program
Based on C. Petzold's sine wave example, outputs a sine wave via the waveOut
API in Win32.
*******************************************************************************/
#include <stdio.h>
#include <windows.h>
#include <math.h>
#include <limits.h>
#include <unistd.h>
#define SAMPLE_RATE 44100
#define FREQ_INIT 440
#define OUT_BUFFER_SIZE 570*4
#define PI 3.14159
#define CHANNELS 2
#define BITS 16
#define MAXTIM 1000000000
double fAngle;
LARGE_INTEGER perffreq;
PWAVEHDR pWaveHdr1, pWaveHdr2;
int iFreq = FREQ_INIT;
VOID FillBuffer (short* pBuffer, int iFreq)
{
int i;
int c;
for (i = 0 ; i < OUT_BUFFER_SIZE ; i += CHANNELS) {
for (c = 0; c < CHANNELS; c++)
pBuffer[i+c] = (short)(SHRT_MAX*sin (fAngle));
fAngle += 2*PI*iFreq/SAMPLE_RATE;
if (fAngle > 2 * PI) fAngle -= 2*PI;
}
}
double elapsed(LARGE_INTEGER t)
{
LARGE_INTEGER rt;
long tt;
QueryPerformanceCounter(&rt);
tt = rt.QuadPart-t.QuadPart;
return (tt*(1.0/(double)perffreq.QuadPart));
}
void CALLBACK waveOutProc(HWAVEOUT hwo, UINT uMsg, DWORD_PTR dwInstance, DWORD_PTR dwParam1, DWORD_PTR dwParam2)
{
if (uMsg == WOM_DONE) {
if (pWaveHdr1->dwFlags & WHDR_DONE) {
FillBuffer((short*)pWaveHdr1->lpData, iFreq);
waveOutWrite(hwo, pWaveHdr1, sizeof(WAVEHDR));
}
if (pWaveHdr2->dwFlags & WHDR_DONE) {
FillBuffer((short*)pWaveHdr2->lpData, iFreq);
waveOutWrite(hwo, pWaveHdr2, sizeof(WAVEHDR));
}
}
}
int main()
{
HWAVEOUT hWaveOut ;
short* pBuffer1;
short* pBuffer2;
short* pBuffer3;
WAVEFORMATEX waveformat;
UINT wReturn;
int bytes;
long t;
LARGE_INTEGER rt;
double timprep;
double filtim;
double waveouttim;
printf("Sine wave output program\n");
fAngle = 0; /* start sine angle */
QueryPerformanceFrequency(&perffreq);
pWaveHdr1 = malloc (sizeof (WAVEHDR));
pWaveHdr2 = malloc (sizeof (WAVEHDR));
pBuffer1 = malloc (OUT_BUFFER_SIZE*sizeof(short));
pBuffer2 = malloc (OUT_BUFFER_SIZE*sizeof(short));
pBuffer3 = malloc (OUT_BUFFER_SIZE*sizeof(short));
if (!pWaveHdr1 || !pWaveHdr2 || !pBuffer1 || !pBuffer2) {
if (!pWaveHdr1) free (pWaveHdr1) ;
if (!pWaveHdr2) free (pWaveHdr2) ;
if (!pBuffer1) free (pBuffer1) ;
if (!pBuffer2) free (pBuffer2) ;
fprintf(stderr, "*** Error: No memory\n");
exit(1);
}
// Load prime parameters to format
waveformat.wFormatTag = WAVE_FORMAT_PCM;
waveformat.nChannels = CHANNELS;
waveformat.nSamplesPerSec = SAMPLE_RATE;
waveformat.wBitsPerSample = BITS;
waveformat.cbSize = 0;
// Calculate other parameters
bytes = waveformat.wBitsPerSample/8; /* find bytes per sample */
if (waveformat.wBitsPerSample&8) bytes++; /* round up */
bytes *= waveformat.nChannels; /* find total channels size */
waveformat.nBlockAlign = bytes; /* set block align */
/* find average bytes/sec */
waveformat.nAvgBytesPerSec = bytes*waveformat.nSamplesPerSec;
printf("Channels: %d\n", waveformat.nChannels);
printf("Sample rate: %d\n", waveformat.nSamplesPerSec);
printf("Bytes per second: %d\n", waveformat.nAvgBytesPerSec);
printf("Block align: %d\n", waveformat.nBlockAlign);
printf("Bits per sample: %d\n", waveformat.wBitsPerSample);
printf("Time per buffer: %f\n",
OUT_BUFFER_SIZE*sizeof(short)/(double)waveformat.nAvgBytesPerSec);
if (waveOutOpen (&hWaveOut, WAVE_MAPPER, &waveformat, (DWORD_PTR)waveOutProc, 0, CALLBACK_FUNCTION)
!= MMSYSERR_NOERROR) {
free (pWaveHdr1) ;
free (pWaveHdr2) ;
free (pBuffer1) ;
free (pBuffer2) ;
hWaveOut = NULL ;
fprintf(stderr, "*** Error: No memory\n");
exit(1);
}
// Set up headers and prepare them
pWaveHdr1->lpData = (LPSTR)pBuffer1;
pWaveHdr1->dwBufferLength = OUT_BUFFER_SIZE*sizeof(short);
pWaveHdr1->dwBytesRecorded = 0;
pWaveHdr1->dwUser = 0;
pWaveHdr1->dwFlags = WHDR_DONE;
pWaveHdr1->dwLoops = 1;
pWaveHdr1->lpNext = NULL;
pWaveHdr1->reserved = 0;
QueryPerformanceCounter(&rt);
waveOutPrepareHeader(hWaveOut, pWaveHdr1, sizeof (WAVEHDR));
timprep = elapsed(rt);
pWaveHdr2->lpData = (LPSTR)pBuffer2;
pWaveHdr2->dwBufferLength = OUT_BUFFER_SIZE*sizeof(short);
pWaveHdr2->dwBytesRecorded = 0;
pWaveHdr2->dwUser = 0;
pWaveHdr2->dwFlags = WHDR_DONE;
pWaveHdr2->dwLoops = 1;
pWaveHdr2->lpNext = NULL;
pWaveHdr2->reserved = 0;
waveOutPrepareHeader(hWaveOut, pWaveHdr2, sizeof (WAVEHDR));
// Send two buffers to waveform output device
QueryPerformanceCounter(&rt);
FillBuffer (pBuffer1, iFreq);
filtim = elapsed(rt);
QueryPerformanceCounter(&rt);
waveOutWrite (hWaveOut, pWaveHdr1, sizeof (WAVEHDR));
waveouttim = elapsed(rt);
FillBuffer (pBuffer2, iFreq);
waveOutWrite (hWaveOut, pWaveHdr2, sizeof (WAVEHDR));
// Run waveform loop
sleep(10);
printf("Total time prepare header: %.10f usec\n", timprep*1000000);
printf("Total time to fill: %.10f usec\n", filtim*1000000);
printf("Total time for waveOutWrite: %.10f usec\n", waveouttim*1000000);
waveOutUnprepareHeader(hWaveOut, pWaveHdr1, sizeof (WAVEHDR));
waveOutUnprepareHeader(hWaveOut, pWaveHdr2, sizeof (WAVEHDR));
// Close waveform file
free (pWaveHdr1) ;
free (pWaveHdr2) ;
free (pBuffer1) ;
free (pBuffer2) ;
}

Related

sending audio via bluetooth a2dp source esp32

I am trying to send measured i2s analogue signal (e.g. from mic) to the sink device via Bluetooth instead of the default noise.
Currently I am trying to change the bt_app_a2d_data_cb()
static int32_t bt_app_a2d_data_cb(uint8_t *data, int32_t i2s_read_len)
{
if (i2s_read_len < 0 || data == NULL) {
return 0;
}
char* i2s_read_buff = (char*) calloc(i2s_read_len, sizeof(char));
bytes_read = 0;
i2s_adc_enable(I2S_NUM_0);
while(bytes_read == 0)
{
i2s_read(I2S_NUM_0, i2s_read_buff, i2s_read_len,&bytes_read, portMAX_DELAY);
}
i2s_adc_disable(I2S_NUM_0);
// taking care of the watchdog//
TIMERG0.wdt_wprotect=TIMG_WDT_WKEY_VALUE;
TIMERG0.wdt_feed=1;
TIMERG0.wdt_wprotect=0;
uint32_t j = 0;
uint16_t dac_value = 0;
// change 16bit input signal to 8bit
for (int i = 0; i < i2s_read_len; i += 2) {
dac_value = ((((uint16_t) (i2s_read_buff[i + 1] & 0xf) << 8) | ((i2s_read_buff[i + 0]))));
data[j] = (uint8_t) dac_value * 256 / 4096;
j++;
}
// testing for loop
//uint8_t da = 0;
//for (int i = 0; i < i2s_read_len; i++) {
// data[i] = (uint8_t) (i2s_read_buff[i] >> 8);// & 0xff;
// da++;
// if(da>254) da=0;
//}
free(i2s_read_buff);
i2s_read_buff = NULL;
return i2s_read_len;
}
I can hear the sawtooth sound from the sink device.
Any ideas what to do?
your data can be an array of some float digits representing analog signals or analog signal variations, for example, a 32khz sound signal contains 320000 float numbers to define captures sound for every second. if your data have been expected to transmit in offline mode you can prepare your outcoming data in the form of a buffer plus a terminator sign then send buffer by Bluetooth module of sender device which is connected to the proper microcontroller. for the receiving device, if you got terminator character like "\r" you can process incoming buffer e.g. for my case, I had to send a string array of numbers but I often received at most one or two unknown characters and to avoid it I reject it while fulfill receiving container.
how to trim unknown first characters of string in code vision
if you want it in online mode i.e. your data must be transmitted and played concurrently. you must consider delays and reasonable time to process for all microcontrollers and devices like Bluetooth, EEprom iCs and...
I'm also working on a project "a2dp source esp32".
I'm playing a wav-file from spiffs.
If the wav-file is 44100, 16-bit, stereo then you can directly write a stream of bytes from the file to the array data[ ].
When I tried to write less data than in the len-variable and return less (for example 88), I got an error, now I'm trying to figure out how to reduce this buffer because of big latency (len=512).
Also, the data in the array data[ ] is stored as stereo.
Example: read data from file to data[ ]-array:
size_t read;
read = fread((void*) data, 1, len, fwave);//fwave is a file
if(read<len){//If get EOF, go to begin of the file
fseek(fwave , 0x2C , SEEK_SET);//skip wav-header 44bytesт
read = fread((void*) (&(data[read])), 1, len-read, fwave);//read up
}
If file mono, I convert it to stereo like this (I read half and then double data):
int32_t lenHalf=len/2;
read = fread((void*) data, 1, lenHalf, fwave);
if(read<lenHalf){
fseek(fwave , 0x2C , SEEK_SET);//skip wav-header 44bytesт
read = fread((void*) (&(data[read])), 1, lenHalf-read, fwave);//read up
}
//copy to the second channel
uint16_t *data16=(uint16_t*)data;
for (int i = lenHalf/2-1; i >= 0; i--) {
data16[(i << 1)] = data16[i];
data16[(i << 1) + 1] = data16[i];
}
I think you have got sawtooth sound because:
your data is mono?
in your "return i2s_read_len;" i2s_read_len less than len
you // change 16bit input signal to 8bit, in the array data[ ] data as 16-bit: 2ByteLeft-2ByteRight-2ByteLeft-2ByteRight-...
I'm not sure, it's a guess.

Write data to an SD card through a buffer without a race condition

I am writing firmware for a data logging device. It reads data from sensors at 20 Hz and writes data to an SD card. However, the time to write data to SD card is not consistent (about 200-300 ms). Thus one solution is writing data to a buffer at a consistent rate (using a timer interrupt), and have a second thread that writes data to the SD card when the buffer is full.
Here is my naive implementation:
#define N 64
char buffer[N];
int count;
ISR() {
if (count < N) {
char a = analogRead(A0);
buffer[count] = a;
count = count + 1;
}
}
void loop() {
if (count == N) {
myFile.open("data.csv", FILE_WRITE);
int i = 0;
for (i = 0; i < N; i++) {
myFile.print(buffer[i]);
}
myFile.close();
count = 0;
}
}
The code has the following problems:
Writing data to the SD card is blocking reading when the buffer is full
It might have a race conditions.
What is the best way to solve this problem? Using a circular buffer, or double buffering? How do I ensure that a race condition does not happen?
You have rather answered your own question; you should use either double buffering or a circular buffer. Double-buffering is probably simpler to implement and appropriate for devices such as an SD card for which block-writes are generally more efficient.
Buffer length selection may need some consideration; generally you would make the buffer the same as the SD sector buffer size (typically 512 bytes), but that may not be practical, and with a sample rate as low as 20 sps, optimising SD write performance is perhaps not an issue.
Another consideration is that you need to match your sample rate to the file-system latency by selecting an appropriate buffer size. In this case the 64 sample buffer buffer will fill in a little more than three seconds, but the block write takes only up-to 300 ms - so you could use a much smaller buffer if required - 8 samples would be sufficient - although be careful, you may have observed latency of 300 ms, but it may be larger when specific boundaries are crossed in the physical flash memory - I have seen significant latency on some cards at 1 Mbyte boundaries - moreover card performance varies significantly between sizes and manufacturers.
An adaptation of your implementation with double-buffering is below. I have reduced the buffer length to 32 samples, but with double-buffering the total is unchanged at 64, but the write lag is reduced to 1.6 seconds.
// Double buffer and its management data/constants
static volatile char buffer[2][32];
static const int BUFFLEN = sizeof(buffer[0]);
static const unsigned char EMPTY = 0xff;
static volatile unsigned char inbuffer = 0;
static volatile unsigned char outbuffer = EMPTY;
ISR()
{
static int count = 0;
// Write to current buffer
char a = analogRead(A0);
buffer[inbuffer][count] = a;
count++ ;
// If buffer full...
if( count >= BUFFLEN )
{
// Signal to loop() that data available (not EMPTY)
outbuffer = inbuffer;
// Toggle input buffer
inbuffer = inbuffer == 0 ? 1 : 0;
count = 0;
}
}
void loop()
{
// If buffer available...
if( outbuffer != EMPTY )
{
// Write buffer
myFile.open("data.csv", FILE_WRITE);
for( int i = 0; i < BUFFLEN; i++)
{
myFile.print(buffer[outbuffer][i]);
}
myFile.close();
// Set the buffer to empty
outbuffer = EMPTY;
}
}
Note the use of volatile and unsigned char for the shared data. It is important that data shared between concurrent execution contexts is accessed explicitly and atomically; access to an int on 8-bit AVR based Arduino requires multiple machine instructions and the interrupt may occur part way through a read/write in loop() and cause an incorrect value to be read.

Converting 24 bit USB audio stream into 32 bit stream

I'm trying to convert a 24 bit usb audio stream into a 32 bit stream so my microcontroller's peripherals can play happily with the stream (it can only handle 16 or 32 bit data like most mcus...).
The following code is what I got from the mcu's company... didn't work as expected and I ended up getting really distorted audio.
// Function takes usb stream and processes the data for our peripherals
// #data - usb stream data
// #byte_count - size of stream
void process_usb_stream(uint8_t *data, uint16_t byte_count) {
// Etc code that gets buffers ready to read the stream...
// Conversion here!
int32_t *buffer;
int sample_count = 0;
for (int i = 0; i < byte_count; i += 3) {
buffer[sample_count++] = data[i] | data[i+1] << 8 | data[i+2] << 16;
}
// Send buffer to peripherals for them to use...
}
Any help with converting the data from a 24 bit stream to 32 bit stream would be super awesome! This area of work is very hard for me :(
data[...] is a uint8_t. You need to cast that before shifting, because data[...]<<8 and data[...]<<16 are undefined. They'll either be 0 or unchanged, neither of which is what you want.
Also, you need to shift by another 8 bits to get the full range and put the sign bit in the right place.
Also, you're treating the data as if it were in little-endian format. Make sure it is. I'll assume that's correct, so something like this works:
int32_t *buffer;
int sample_count = 0;
for (int i = 0; i+3 <= byte_count; ) {
int32_t v = ((int32_t)data[i++])<<8;
v |= ((int32_t)data[i++])<<16;
v |= ((int32_t)data[i++])<<24;
buffer[sample_count++] = v;
}
Finally, note that this assumes that byte_count is divisible by 3 -- make sure that's true!
this is DSP stuff if, also post this question on http://dsp.stackexchange.com
In DSP the process of changing the bit depth is called scaling
16 bit resolution has 65536 values
24 bit resolution has 16777216
possible values
32 bit has 4294967296 values so the factor is 256
According to https://electronics.stackexchange.com/questions/229268/what-is-name-of-process-used-to-change-sample-bit-depth/229271
reduction from 24 bit to 16 bit is called scaling down and is done by dividing each value by 256.
This can be done by bitwise shifting every bit by 8
y = x >> 8. When scaling down this way the LSB is lost
Scaling up to 32 bit is more complicated and there are several approaches how to do this. It may work by multiplying each bit of the value with a value between 2⁰ and 2⁸.
Push the 24 bit value in a 32 bit register and then left-shifting each bit by a value between 2⁰ and 2⁸:
data32[31] = data32[23] << 8;
data32[22] = data32[14] << 8;
...
data32[0] = data32[0];
and interpolate the bits you do not get with this (linear interpolation)
Maybe there are much better scaling up algortihms ask on http://dsp.stackexchange.com
See also http://blog.bjornroche.com/2013/05/the-abcs-of-pcm-uncompressed-digital.html for the scaling up problem...

Large overhead in CUDA kernel launch outside GPU execution

I am measuring the running time of kernels, as seen from a CPU thread, by measuring the interval from before launching a kernel to after a cudaDeviceSynchronize (using gettimeofday). I have a cudaDeviceSynchronize before I start recording the interval. I also instrument the kernels to record the timestamp on the GPU (using clock64) at the start of the kernel by thread(0,0,0) of each block from block(0,0,0) to block(occupancy-1,0,0) to an array of size equal to number of SMs. Every thread at the end of the kernel code, updates the timestamp to another array (of the same size) at the index equal to the index of the SM it runs on.
The intervals calculated from the two arrays are 60-70% of that measured from the CPU thread.
For example, on a K40, while gettimeofday gives an interval of 140ms, the avg of intervals calculated from GPU timestamps is only 100ms. I have experimented with many grid sizes (15 blocks to 6K blocks) but have found similar behavior so far.
__global__ void some_kernel(long long *d_start, long long *d_end){
if(threadIdx.x==0){
d_start[blockIdx.x] = clock64();
}
//some_kernel code
d_end[blockIdx.x] = clock64();
}
Does this seem possible to the experts?
Does this seem possible to the experts?
I suppose anything is possible for code you haven't shown. After all, you may just have a silly bug in any of your computation arithmetic. But if the question is "is it sensible that there should be 40ms of unaccounted-for time overhead on a kernel launch, for a kernel that takes ~140ms to execute?" I would say no.
I believe the method I outlined in the comments is reasonably accurate. Take the minimum clock64() timestamp from any thread in the grid (but see note below regarding SM restriction). Compare it to the maximum time stamp of any thread in the grid. The difference will be comparable to the reported execution time of gettimeofday() to within 2 percent, according to my testing.
Here is my test case:
$ cat t1040.cu
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#define LS_MAX 2000000000U
#define MAX_SM 64
#define cudaCheckErrors(msg) \
do { \
cudaError_t __err = cudaGetLastError(); \
if (__err != cudaSuccess) { \
fprintf(stderr, "Fatal error: %s (%s at %s:%d)\n", \
msg, cudaGetErrorString(__err), \
__FILE__, __LINE__); \
fprintf(stderr, "*** FAILED - ABORTING\n"); \
exit(1); \
} \
} while (0)
#include <time.h>
#include <sys/time.h>
#define USECPSEC 1000000ULL
__device__ int result;
__device__ unsigned long long t_start[MAX_SM];
__device__ unsigned long long t_end[MAX_SM];
unsigned long long dtime_usec(unsigned long long start){
timeval tv;
gettimeofday(&tv, 0);
return ((tv.tv_sec*USECPSEC)+tv.tv_usec)-start;
}
__device__ __inline__ uint32_t __mysmid(){
uint32_t smid;
asm volatile("mov.u32 %0, %%smid;" : "=r"(smid));
return smid;}
__global__ void kernel(unsigned ls){
unsigned long long int ts = clock64();
unsigned my_sm = __mysmid();
atomicMin(t_start+my_sm, ts);
// junk code to waste time
int tv = ts&0x1F;
for (unsigned i = 0; i < ls; i++){
tv &= (ts+i);}
result = tv;
// end of junk code
ts = clock64();
atomicMax(t_end+my_sm, ts);
}
// optional command line parameter 1 = kernel duration, parameter 2 = number of blocks, parameter 3 = number of threads per block
int main(int argc, char *argv[]){
unsigned ls;
if (argc > 1) ls = atoi(argv[1]);
else ls = 1000000;
if (ls > LS_MAX) ls = LS_MAX;
int num_sms = 0;
cudaDeviceGetAttribute(&num_sms, cudaDevAttrMultiProcessorCount, 0);
cudaCheckErrors("cuda get attribute fail");
int gpu_clk = 0;
cudaDeviceGetAttribute(&gpu_clk, cudaDevAttrClockRate, 0);
if ((num_sms < 1) || (num_sms > MAX_SM)) {printf("invalid sm count: %d\n", num_sms); return 1;}
unsigned blks;
if (argc > 2) blks = atoi(argv[2]);
else blks = num_sms;
if ((blks < 1) || (blks > 0x3FFFFFFF)) {printf("invalid blocks: %d\n", blks); return 1;}
unsigned ntpb;
if (argc > 3) ntpb = atoi(argv[3]);
else ntpb = 256;
if ((ntpb < 1) || (ntpb > 1024)) {printf("invalid threads: %d\n", ntpb); return 1;}
kernel<<<1,1>>>(100); // warm up
cudaDeviceSynchronize();
cudaCheckErrors("kernel fail");
unsigned long long *h_start, *h_end;
h_start = new unsigned long long[num_sms];
h_end = new unsigned long long[num_sms];
for (int i = 0; i < num_sms; i++){
h_start[i] = 0xFFFFFFFFFFFFFFFFULL;
h_end[i] = 0;}
cudaMemcpyToSymbol(t_start, h_start, num_sms*sizeof(unsigned long long));
cudaMemcpyToSymbol(t_end, h_end, num_sms*sizeof(unsigned long long));
unsigned long long htime = dtime_usec(0);
kernel<<<blks,ntpb>>>(ls);
cudaDeviceSynchronize();
htime = dtime_usec(htime);
cudaMemcpyFromSymbol(h_start, t_start, num_sms*sizeof(unsigned long long));
cudaMemcpyFromSymbol(h_end, t_end, num_sms*sizeof(unsigned long long));
cudaCheckErrors("some error");
printf("host elapsed time (ms): %f \n device sm clocks:\n start:", htime/1000.0f);
unsigned long long max_diff = 0;
for (int i = 0; i < num_sms; i++) {printf(" %12lu ", h_start[i]);}
printf("\n end: ");
for (int i = 0; i < num_sms; i++) {printf(" %12lu ", h_end[i]);}
for (int i = 0; i < num_sms; i++) if ((h_start[i] != 0xFFFFFFFFFFFFFFFFULL) && (h_end[i] != 0) && ((h_end[i]-h_start[i]) > max_diff)) max_diff=(h_end[i]-h_start[i]);
printf("\n max diff clks: %lu\nmax diff kernel time (ms): %f\n", max_diff, max_diff/(float)(gpu_clk));
return 0;
}
$ nvcc -o t1040 t1040.cu -arch=sm_35
$ ./t1040 1000000 1000 128
host elapsed time (ms): 2128.818115
device sm clocks:
start: 3484744 3484724
end: 2219687393 2228431323
max diff clks: 2224946599
max diff kernel time (ms): 2128.117432
$
Notes:
This code can only be run on a cc3.5 or higher GPU due to the use of 64-bit atomicMin and atomicMax.
I've run it on a variety of grid configurations, on both a GT640 (very low end cc3.5 device) and K40c (high end) and the timing results between host and device agree to within 2% (for reasonably long kernel execution times. If you pass 1 as the command line parameter, with very small grid sizes, the kernel execution time will be very short (nanoseconds) whereas the host will see about 10-20us. This is kernel launch overhead being measured. So the 2% number is for kernels that take much longer than 20us to execute).
It accepts 3 (optional) command line parameters, the first of which varies the amount of time the kernel will execute.
My timestamping is done on a per-SM basis, because the clock64() resource is indicated to be a per-SM resource. The sm clocks are not guaranteed to be synchronized between SMs.
You can modify the grid dimensions. The second optional command line parameter specifies the number of blocks to launch. The third optional command line parameter specifies the number of threads per block. The timing methodology I have shown here should not be dependent on number of blocks launched or number of threads per block. If you specify fewer blocks than SMs, the code should ignore "unused" SM data.

CUDA performance test

I'm writing a simple CUDA program for performance test.
This is not related to vector calculation, but just for a simple (parallel) string conversion.
#include <stdio.h>
#include <string.h>
#include <cuda_runtime.h>
#define UCHAR unsigned char
#define UINT32 unsigned long int
#define CTX_SIZE sizeof(aes_context)
#define DOCU_SIZE 4096
#define TOTAL 100000
#define BBLOCK_SIZE 500
UCHAR pH_TXT[DOCU_SIZE * TOTAL];
UCHAR pH_ENC[DOCU_SIZE * TOTAL];
UCHAR* pD_TXT;
UCHAR* pD_ENC;
__global__
void TEST_Encode( UCHAR *a_input, UCHAR *a_output )
{
UCHAR *input;
UCHAR *output;
input = &(a_input[threadIdx.x * DOCU_SIZE]);
output = &(a_output[threadIdx.x * DOCU_SIZE]);
for ( int i = 0 ; i < 30 ; i++ ) {
if ( (input[i] >= 'a') && (input[i] <= 'z') ) {
output[i] = input[i] - 'a' + 'A';
}
else {
output[i] = input[i];
}
}
}
int main(int argc, char** argv)
{
struct cudaDeviceProp xCUDEV;
cudaGetDeviceProperties(&xCUDEV, 0);
// Prepare Source
memset(pH_TXT, 0x00, DOCU_SIZE * TOTAL);
for ( int i = 0 ; i < TOTAL ; i++ ) {
strcpy((char*)pH_TXT + (i * DOCU_SIZE), "hello world, i need an apple.");
}
// Allocate vectors in device memory
cudaMalloc((void**)&pD_TXT, DOCU_SIZE * TOTAL);
cudaMalloc((void**)&pD_ENC, DOCU_SIZE * TOTAL);
// Copy vectors from host memory to device memory
cudaMemcpy(pD_TXT, pH_TXT, DOCU_SIZE * TOTAL, cudaMemcpyHostToDevice);
// Invoke kernel
int threadsPerBlock = BLOCK_SIZE;
int blocksPerGrid = (TOTAL + threadsPerBlock - 1) / threadsPerBlock;
printf("Total Task is %d\n", TOTAL);
printf("block size is %d\n", threadsPerBlock);
printf("repeat cnt is %d\n", blocksPerGrid);
TEST_Encode<<<blocksPerGrid, threadsPerBlock>>>(pD_TXT, pD_ENC);
cudaMemcpy(pH_ENC, pD_ENC, DOCU_SIZE * TOTAL, cudaMemcpyDeviceToHost);
// Free device memory
if (pD_TXT) cudaFree(pD_TXT);
if (pD_ENC) cudaFree(pD_ENC);
cudaDeviceReset();
}
And when i change BLOCK_SIZE value from 2 to 1000, I got a following duration time (from NVIDIA Visual Profiler)
TOTAL BLOCKS BLOCK_SIZE Duration(ms)
100000 50000 2 28.22
100000 10000 10 22.223
100000 2000 50 12.3
100000 1000 100 9.624
100000 500 200 10.755
100000 250 400 29.824
100000 200 500 39.67
100000 100 1000 81.268
My GPU is GeForce GT520 and max threadsPerBlock value is 1024, so I predicted that I would get best performance when BLOCK is 1000, but the above table shows different result.
I can't understand why Duration time is not linear, and how can I fix this problem. (or how can I find optimized Block value (mimimum Duration time)
It seems 2, 10, 50 threads doesn't utilize the capabilities of the gpu since its design is to start much more threads.
Your card has compute capability 2.1.
Maximum number of resident threads per multiprocessor = 1536
Maximum number of threads per block = 1024
Maximum number of resident blocks per multiprocessor = 8
Warp size = 32
There are two issues:
1.
You try to occupy so much register memory per thread that it will definetly is outsourced to slow local memory space if your block sizes increases.
2.
Perform your tests with multiple of 32 since this is the warp size of your card and many memory operations are optimized for thread sizes with multiple of the warp size.
So if you use only around 1024 (1000 in your case) threads per block 33% of your gpu is idle since only 1 block can be assigned per SM.
What happens if you use the following 100% occupancy sizes?
128 = 12 blocks -> since only 8 can be resident per sm the block execution is serialized
192 = 8 resident blocks per sm
256 = 6 resident blocks per sm
512 = 3 resident blocks per sm

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