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That's just plain incorrect: > Through also measuring the execution time and peak memory usage, we were able to relate both to energy to understand not only ho
by skohan 4y ago
That's just plain incorrect:
> Through also measuring the execution time and peak memory usage, we were able to relate both to energy to understand not only how memory usage affects energy con- sumption, but also how time and energy relate. This allowed us to understand if a faster language is always the most energy efficient. As we saw, this is not always the case.
- nindalf 4y agoNo doubt you read the graphs right after this statement? Look at the green dots (the ratio between energy consumption and time taken). Nearly all languages have comparable ratios, meaning a lower execution time leads to less energy consumed. > this is not always the case Just almost all the time, with a few exceptions. Execution time and energy consumption are very strongly correlated. Time taken is the single biggest factor in how much power is consumed in modern CPUs. The idea is to complete any task quickly and put the idle cores to sleep to conserve power.
- skohan 4y agoIt's explicitly a non-conclusion that there is a deterministic relationship between speed of execution and energy consumption as your initial comment implies. > Execution time behaves differently when compared to en- ergy efficiency. The results for the 3 benchmarks presented in Table 3 (and the remainder shown in the appendix) show several scenarios where a certain language energy consump- tion rank differs from the execution time rank (as the arrows in the first column indicate). In the fasta benchmark, for example, the Fortran language is second most energy effi- cient, while dropping 6 positions when it comes to execution time. Moreover, by observing the Ratio values in Figures 1 to 3 (and the remainder in the appendix under Results - C. En- ergy and Time Graphs), we clearly see a substantial variation between languages. This means that the average power is not constant, which further strengthens the previous point. There is a strong correlation, yes, which makes sense because more time will likely correlate to more work done by the hardware. However the paper proves that there are exceptions to this rule. That's interesting given that most people, including you, would have flatly assumed that performance is a proxy for energy efficiency. You could argue that it's not a finding which is going to be relevant to most software engineers, but it might be interesting if you are designing or implementing a programming language for instance.
- nindalf 4y agoSo there is a very strong correlation between time taken and energy consumption. This is because less work is done (like you pointed out) and CPUs go back to idle quicker (like I did). This part is blindingly obvious. There are a few exceptions, but no mechanism that explains that from the paper. So statistical noise. If anyone is designing a language to be energy efficient, they would do what is obvious - do less work by generating more efficient code (like you said) or make it easy to parallelise work so cores can go back to sleep quicker (like I said). They’re not going to design for something statistical anomalies.
- skohan 4y agoIt’s a computer science paper. They don’t have to present an actionable solution for it to provide value. They have a meaningful new finding, which may provide the missing piece to some solution later on. If we disregarded all scientific inquiry which did not result in an immediate solution to an existing problem, computers probably would not even have been invented by now.
- nindalf 4y agoThe “meaningful new finding” is statistical noise that only affects a few data points. You’ve written hundreds of words without addressing that core issue. Eager to hear your thoughts on this once you’ve organised them.