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It's interesting that there appears to be a trade-off between using parallelism to reduce response time and optimizing for power usage, specifically in the use
by dkarl 17y ago
It's interesting that there appears to be a trade-off between using parallelism to reduce response time and optimizing for power usage, specifically in the use of redundant computations to avoid communication between nodes (as mentioned in the Guy Steele slides posted earlier.) Precomputing information a user might request is another potential power-waster that can be very good for responsiveness. My first reaction: man, I have enough environmental dilemmas in my life already! Will I have to turn on "high latency mode" in my applications just like I turn off my low-flow showerhead while I'm lathering up?
- chipsy 17y agoWhen you start seriously optimizing, you're always making a tradeoff. At first, you start moving from sloppy naive algorithms to more specific ones. No big problem there. Then you go from the general-case algorithm to a "tuned" one that biases to your specific situation. Maybe you change to data types that your language can optimize better. Then you start playing directly with memory and you have to think about little things like byte alignments, pipelining and cache size, getting more and more specific to the architecture you are running on. At each step, the nature of the solution gets a little bit more intertwined with the details. Parallelization becomes a tradeoff you "feel" much earlier, because you're changing things all the way up at the algorithm level.