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→Design of Your Tests
[[Category:SPO600 Labs]]{{Admon/lab|Purpose of this Lab|In this lab, you will investigate the impact of different algorithms which produce the same effect. You will test and select one of two three algorithms for adjusting the volume of PCM audio samples based on benchmarking of two possible approaches.}}
== Lab 6 4 ==
=== Background:===* Digital sound is typically represented, uncompressed, as signed 16-bit integer signal samples. There is one stream are two streams of samples , one each for the left and right stereo channels, at typical sample rates of 44.1 or 48 thousand samples per secondper channel, for a total of 88.2 or 96 thousand samples per second(kHz). Since there are 16 bits (2 bytes) per sample, the data rate is 88.2 * 1000 * 2 = 176,400 bytes/second (~172 KiB/sec) or 96 * 1000 * 2 = 192,000 bytes/second (~187.5 KiB/sec).* To change the volume of sound, each sample can be scaled by a volume factor, in the range of 0.0000 00 (silence) to 1.0000 00 (silence to full volume).
* On a mobile device, the amount of processing required to scale sound will affect battery life.
=== Basic Sound Scale Program ===
# Pre-calculate a lookup table (array) of all possible sample values multiplied by the volume factor, and look up each sample in that table to get the scaled values. (You'll have to handle the fact that the input values range from -32768 to +32767, while C arrays accept only a positive index).
# Convert the volume factor 0.75 to a fix-point integer by multiplying by a binary number representing a fixed-point value "1". For example, you could use 0b100000000 (= 256 in decimal) to represent 1.00, and therefore use 0.75 * 256 = 192 for your volume factor. Multiply this fixed-point integer volume factor by each sample, then shift the result to the right the required number of bits after the multiplication (>>8 if you're using 256 as the multiplier).
Important! -- explain what you're doing so that a reader coming across your blog post understands the context (in other words, don't just jump into a discussion of optimization results -- give your post some context).
=== Things to consider ===
==== Design of Your Test Tests ====
* Most solutions for a problem of this type involve generating a large amount of data in an array, processing that array using the function being evaluated, and then storing that data back into an array. Make sure that you measure the time taken in the test function only -- you need to be able to remove the rest of the processing time from your evaluation.
* You may need to run a very large amount of sample data through the function to be able to detect its performance. Feel free to edit the sample count in <code>vol.h</code> as necessary.
* If you do not use the output from your calculation (e.g., do something with the output array), the compiler may recognize that, and remove the code you're trying to test. Be sure to process the results in some way so that the optimizer preserves the code you want to test. It is a good idea to calculate some sort of verification value to ensure that both approaches generate the same results.
==== Analyzing Results ====
* What is the impact of various optimization levels on the software performance?(For example, compiling with -O0 / -O1 / -O2 / -O3)* Does the distribution of data matter?(e.g., is there any difference if there are no absolute large numbers, or no negative numbers?)* If samples are fed at CD rate (44100 samples per second x 2 channelsx 2 bytes per sample), can both each of the algorithms keep up?
* What is the memory footprint of each approach?
* What is the performance of each approach?
* What is the energy consumption of each approach? (What information do you need to calculate this?)
* Aarchie and Betty Various machines within an architecture have very different performance profiles, energy consumption, and hardware costs -- so it's not reasonable to compare performance between the machines, but it is reasonable to compare the relative performance of the two algorithms in each context. Do you get similar resultsDoes the ratio of performance of the various approaches remain constant across the machines? Why or why not?
* What other optimizations can be applied to this problem?
=== Tips ===
{{Admon/tip|Non-Decimal Notation|In this lab, the number prefix 0x indicates a hexadecimal number, and 0b indicates a binary number, in harmony with the C language.}}
{{Admon/tip|Time and Memory Usage of a Program|You can get basic timing information for a program by running <code>time ''programName''</code> -- the output will show the total time taken (real), the amount of CPU time used to run the application (user), and the amount of CPU time used by the operating system on behalf of the application (system).
Another version of the <code>time</code> command, located in <code>/bin/time</code>, gives slightly different information, including maximum resident memory usage: <code>/bin/time ''programName''</code>}}
{{Admon/tip|SOX|If you want to try this with actual sound samples, you can convert a sound file of your choice to raw 16-bit signed integer PCM data using the [http://sox.sourceforge.net/ sox] utility present on most Linux systems and available for a wide range of platforms.}}
{{Admon/tip|Stack Limit|Fixed-size, non-static arrays will be placed in the stack space. The size of the stack space is controlled by per-process limits, inherited from the shell, and adjustable with the <code>ulimit</code> command. Allocating an array larger than the stack size limit will cause a segmentation fault, usually on the first write. To see the current stack limit, use <code>ulimit -s</code> (displayed value is in KB; default is usually 8192 KB or 8 MB). To set the current stack limit, place a new size in KB or the keyword <code>unlimited</code>after the <code>-s</code> argument.<br /><br />Alternate (and preferred) approach, as used in the provided sample code: allocate the array space with <code>malloc()</code> or <code>calloc()</code>.}}
{{Admon/tip|stdint.h|The <code>stdint.h</code> header provides definitions for many specialized integer size types. Use <code>int16_t</code> for 16-bit signed integers.}}