46 Matching Annotations
  1. Dec 2023
    1. There are 5 ways to measure execution time manually in Python using the time module, they are:
      1. Use time.time()
      2. Use time.perf_counter()
      3. Use time.monotonic()
      4. Use time.process_time()
      5. Use time.thread_time()

      Note, each function returns a time in seconds and has an equivalent function that returns the time in nanoseconds, e.g. time.time_ns(), time.perf_counter_ns(), time.monotonic_ns(), time.process_time_ns() and time.thread_time_ns().

      Recall that there are 1,000 nanoseconds in one microsecond, 1,000 microseconds in 1 millisecond, and 1,000 milliseconds in one second. This highlights that the nanosecond versions of the function are for measuring very short time scales indeed.

  2. Nov 2023
    1. Intel processors also support multiple P-states. P0 is the state where the processor is operating at maximum frequency and voltage, and higher-numbered P-states operate at a lower frequency and voltage to reduce power consumption. Processors can have dozens of P-states, but the transitions are controlled by the hardware and OS and so P-states are of less interest to application developers than C-states.

      These exist too, but we can only control them indirectly at best.

    2. Intel processors have aggressive power-saving features. The first is the ability to switch frequently (thousands of times per second) between active and idle states, and there are actually several different kinds of idle states. These different states are called C-states. C0 is the active/busy state, where instructions are being executed. The other states have higher numbers and reflect increasing deeper idle states. The deeper an idle state is, the less power it uses, but the longer it takes to wake up from.

      Mental note: Think "C for the CPU cool down"

  3. Aug 2023
  4. Jul 2023
    1. Go users can create their custom profiles via pprof.Profile and use the existing tools

      do we have any custom implementations of these profiles available publicly

  5. Nov 2022
  6. Sep 2022
    1. Because rbspy is a sampling profiler (not a tracing profiler), it actually can't tell you how times a function was called -- it just reports "hey, I observed your program 100,000 times, and 98,000 of those times it was in the calculate_thing function". ruby-prof is a tracing profiler for Ruby, which can tell you exactly how many times each function was called at the cost of being higher overhead.
    2. it's useful to understand the difference between "self time" and "total time" spent in a function
  7. Aug 2022
  8. Jun 2022
  9. May 2022
  10. Apr 2022
    1. Mathew, D., Giles, J. R., Baxter, A. E., Oldridge, D. A., Greenplate, A. R., Wu, J. E., Alanio, C., Kuri-Cervantes, L., Pampena, M. B., D’Andrea, K., Manne, S., Chen, Z., Huang, Y. J., Reilly, J. P., Weisman, A. R., Ittner, C. A. G., Kuthuru, O., Dougherty, J., Nzingha, K., … Wherry, E. J. (2020). Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications. Science, 369(6508), eabc8511. https://doi.org/10.1126/science.abc8511

  11. Feb 2022
  12. Dec 2021
  13. Jul 2021
    1. Claudia: How long did you live in the States?Yosell: Let's see, about 24 years. Out here in Mexico, I've probably been here for like a year and a half. Just barely, I guess.Claudia: What was it like coming back to Mexico? You said you made the decision on your own?Yosell: Yeah, I mean, I already did know about it just a little bit, so it wasn't too bad. It was just basically like Los Angeles, it's the same thing, really. Just the differences, the corruption out here, and how people treat you. I would probably walk down the street, and I would always get a dirty look or something. I'd always get checked by the cops here, that's a constant thing for me.


  14. Oct 2020
  15. Sep 2020
  16. Jul 2020
    1. ruby-prof supports excluding specific methods and threads from profiling results. This is useful for reducing connectivity in the call graph, making it easier to identify the source of performance problems when using a graph printer. For example, consider Integer#times: it's hardly ever useful to know how much time is spent in the method itself. We are more interested in how much the passed in block contributes to the time spent in the method which contains the Integer#times call. The effect on collected metrics are identical to eliminating methods from the profiling result in a post process step.
  17. May 2020
    1. If you profile your users, you have to tell them. Therefore, you must pick the relevant clause from the privacy policy generator.
    2. In case you’re implementing any ADM process, you have to tell your users.
    3. If you’re selling products and keep record of users’ choices for marketing purposes, dividing them into meaningful categories, such as by age, gender, geographical origin etc., you’re profiling them.
  18. Jan 2019
  19. Oct 2017
    1. ‘themorepredictableresultwouldbeagradualdesertificationoftheculturallifeofindividualsnolongerabletoencounterwhatisunusual,unexpected,andsurprising.’[61]Ratherthanindividualizedbubbles,sharingsegregatessocialnetworkusersintoculturalbubblesofpreferences,products,andknowledge
    2. platformssuchasGoogleandFacebookthatoperatelike‘predictionengines’by‘constantlycreatingandrefiningatheoryofwhoyouareandwhatyou’lldoandwantnext’basedonwhatyouhavedoneandwantedbefore



  20. Sep 2017
    1. In each case data was framed as repressive of notions of civil society or enforcing an impoverished or constrictive notion of citizenship. The perspectives of Tufekci and Cheney-Lippold provide valuable insight into how algorithms and data are powerful shapers of modern life. Yet, they leave little room for a different form of algorithmic citizenship that might emerge where indi-viduals desire to reform technology and data-driven processes. As Couldry and Powell (2014) note, models of algorithmic power (Beer, 2009; Lash, 2007) tend to downplay questions of individual agency. They suggest a need to “highlight not just the risks of creating and sharing data, but the opportunities as well” (p. 5). We should be attentive to moments where meaningful change can occur, even if those changes are fraught with forces of neoliberalism and tinged with technocracy.



  21. Jan 2016