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[[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.}}

=== 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 (multiplied) by a volume factor, in the range of 0.0000 00 (silence) to 1.0000 00 (silence to full volume).

TaskThree approaches to this problem are provided:

# The basic or Naive algorithm (<code>vol1.c</code>). This approach multiplies each sound sample by 0.75, casting from signed 16-bit integer to floating point and back again. Casting between integer and floating point can be [[Expensive|expensive]] operations.# Alookup-based algorithm (<code>vol2.c</code>). Create This approach uses a large pre-calculated table of all 65536 possible results, and looks up each sample in that table instead of multiplying.# A fixed-point algorithm (500M?<code>vol3.c</code>) array of int16_t numbers . This approach uses fixed-point math and bit shifting to represent sound samplesperform the multiplication without using floating-point math.

C. Sum In this lab, ''do not'' compare the results and display relative performance across different machines, because the total (just systems provided have a wide range of processor implementations, from server-class to keep mobile-class. However, ''do'' compare the optimzer from eliminating relative performance of the various algorithms on the scaling code)''same'' machine.

Try using each Review the contents of this archive:* <code>vol.h</code> controls the number of these three approaches samples to step Bbe processed* <code>vol1.c</code>, <code>vol2.c</code>, and compare <code>vol3.c</code> implement the various algorithms* The <code>Makefile</code> can be used to build the results:programs

Perform these steps:# Multiply Unpack the archive <code>/public/spo600-algorithm-selection-lab.tgz</code># Study each sample by of the source code files and make sure that you understand what the floating point volume factor 0code is doing.75# Pre-calculate '''Make a lookup table (array) prediction''' of all possible sample values multiplied by the volume factor, relative performance of each scaling algorithm.# Build and look up test each sample in that table to get of the scaled valuesprograms.# Convert * Do all of the volume factor 0.75 algorithms produce the same output?#** How can you verify this?#** If there is a difference, is it significant enough to a fix-point integer by multiplying by a binary matter?#* Change the number representing of samples so that each program takes a fixed-point value "reasonable amount of time to execute (suggested minimum 20 seconds, 1". For example, you could use 0b100000000 (= 256 in decimalminute or more is better). Shift # Test the result performance of each program.#* Find a way to measure performance ''without'' the right time taken to perform the required number of bits after test setup pre-processing (generating the multiplication samples) and post-processing (>>8 if summing the results) so that youcan measure 're using 256 as 'only'' the time taken to scale the multiplier)samples.'''This is the hard part!'''#* How much time is spent scaling the sound samples?#* Do multiple runs take the same time? How much variation do you observe? What is the likely cause of this variation?#* Is there any difference in the results produced by the various algorithms?#* Does the difference between the algorithms vary depending on the architecture and implementation on which you test?#* What is the relative memory usage of each program?# Was your prediction accurate?

Blog about your results. Important! -- explain what you're doing so that experiments with a reader coming across detailed analysis of your blog post understands the context (in other wordsresults, don't just jump into a discussion of optimization results including memory usage, performance, accuracy, and trade-- give your post some context)offs.

==== 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. The test setup can take more time than the actual test! Make sure that you measure the time taken in the code under test function only -- you need to be able to remove the rest of the processing time from your evaluation.

* You can Be aware of what other tasks the system is handling during your test using actual sound data run, including software running on behalf of other users. === Tips ==={{Admon/tip|Analysis|Do a thorough analysis of the results. Be certain (see and prove!) that your performance measurement ''does not'' include the tips section, below) generation or using generated summarization of the test data. If you're generating data, it is best Do multiple runs and discard the outliers. Decide whether to use a pseudo-random number generator which is seeded with mean, minimum, or maximum time values from the same value every timemultiple runs, and explain why you made that decision. Control your variables well. Show relative performance as percentage change, e.g., so "this approach was NN% faster than that each run processes the same dataapproach".}}* Be aware of what other tasks {{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 system is handling during your test runC language.}}

==== Analyzing Results ====* What is the impact {{Admon/tip|Time and Memory Usage of various optimization levels on a Program|You can get basic timing information for a program by running <code>time ''programName''</code> -- the software performance?* Does output will show the distribution of data matter?* If samples are fed at CD rate total time taken (44100 samples per second x 2 channelsreal), can both algorithms keep up?* What is the memory footprint amount of each approach?* What is the performance of each approach?* What is CPU time used to run the energy consumption of each approach? application (What information do you need to calculate this?user)* Aarchie , and Betty have different performance profiles, so it's not reasonable to compare performance between the machines, but it is reasonable to compare amount of CPU time used by the relative performance operating system on behalf of the two algorithms in each contextapplication (system). Do you get similar results?* What other optimizations can be applied to this problem?

{{Admon/tip|Stack Limitstdint.h|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>ulimitstdint.h</code> command. Allocating an array larger than the stack header provides definitions for many specialized integer 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)types. To set the current stack limit, place a new size in KB or the keyword Use <code>unlimitedint16_t</code>after the <code>for 16-s</code> argument.<br /><br />Alternate (and preferred) approach: allocate the array space with <code>malloc()</code> or <code>calloc()</code>bit signed integers.}}

{{Admon/tip|stdint.hScripting|The <code>stdint.h</code> header provides definitions for many specialized integer size types. Use <code>int16_t</code> for 16-bit signed integers.bash scripting capabilities to reduce tedious manual steps!}}