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Created page with 'Category:SPO600 Labs{{Admon/lab|Purpose of this Lab|In this lab, you will select one of two algorithms for adjusting the volume of PCM audio samples based on benchmarking of …'
[[Category:SPO600 Labs]]{{Admon/lab|Purpose of this Lab|In this lab, you will select one of two algorithms for adjusting the volume of PCM audio samples based on benchmarking of two possible approaches.}}
== Lab 3 ==
1. Write two different approaches to adjusting the volume of a sequence of sound samples:
* The first one should scale a signed 16-bit integer by multiplying it by a volume scaling factor expressed as a floating point number in the range of 0-1.
* The second one should do the same thing, using a lookup table (a pre-computed array of all 65536 possible values). The lookup table should be initialized every time a different volume factor is used.
2. Test which approach is faster. Control the variables and use a large run of data (at least millions of samples). Use both [[SPO600 Servers|Xerxes and Aarchie]] for testing.
3. Blog about your results. 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 ===
* Does the distribution of data matter?
* If samples are fed at CD rate (44100 samples per second x 2 channels), can both 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?
* Xerxes and Aarchie have different performance profiles, 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 results?
* What other optimizations can be applied to this problem?
=== Competition ===
* How fast can you scale 100 million int16 PCM sound samples?
== Lab 3 ==
1. Write two different approaches to adjusting the volume of a sequence of sound samples:
* The first one should scale a signed 16-bit integer by multiplying it by a volume scaling factor expressed as a floating point number in the range of 0-1.
* The second one should do the same thing, using a lookup table (a pre-computed array of all 65536 possible values). The lookup table should be initialized every time a different volume factor is used.
2. Test which approach is faster. Control the variables and use a large run of data (at least millions of samples). Use both [[SPO600 Servers|Xerxes and Aarchie]] for testing.
3. Blog about your results. 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 ===
* Does the distribution of data matter?
* If samples are fed at CD rate (44100 samples per second x 2 channels), can both 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?
* Xerxes and Aarchie have different performance profiles, 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 results?
* What other optimizations can be applied to this problem?
=== Competition ===
* How fast can you scale 100 million int16 PCM sound samples?
