benchmarking | 易学教程

How do you time a function in Go and return its runtime in milliseconds?

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问题 How do you time a function in Go and return its runtime in milliseconds? 回答1: Use the Go testing package to benchmark the function. For example, package main import ( "fmt" "testing" ) // the function to be benchmarked func Function(n int) int64 { n64 := int64(n) return n64 * n64 } func BenchmarkFunction(b *testing.B) { n := 42 for i := 0; i < b.N; i++ { _ = Function(n) } } func main() { br := testing.Benchmark(BenchmarkFunction) fmt.Println(br) } Output: 500000000 4.22 ns/op You can also use

Anyone here has benchmarked Intel C++ compiler and GCC?

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问题 I am not sure whether I should post this question here, because this seems to be a programming-oriented website. Anyway, I think there must be some gurus here who knows this. Now I have a AMD Opteron server running CentOS 5. I want to have a compiler for a fairly large c++ Boost based program. Which compiler I should choose? 回答1: I hope this helps more than hurts :) I did a little compiler shootout sometime over a year ago, and I am going off memory. GCC 4.2 (Apple) Intel 10 GCC 4.2 (Apple) +

Why does JavaScript appear to be 4 times faster than C++?

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问题 For a long time, I had thought of C++ being faster than JavaScript. However, today I made a benchmark script to compare the speed of floating point calculations in the two languages and the result is amazing! JavaScript appears to be almost 4 times faster than C++! I let both of the languages to do the same job on my i5-430M laptop, performing a = a + b for 100000000 times. C++ takes about 410 ms, while JavaScript takes only about 120 ms. I really do not have any idea why JavaScript runs so

Measure and Benchmark Time for Ruby Methods

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问题 How can i measure the time taken by a method and the individual statements in that method in Ruby. If you see the below method i want to measure the total time taken by the method and the time taken for database access and redis access. I do not want to write Benchmark.measure before every statement. Does the ruby interpreter gives us any hooks for doing this ? def foo # code to access database # code to access redis. end 回答1: You could use the Time object. (Time Docs) For example, start =

What's really more performant? Haskell or OCaml [closed]

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问题 As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance. Closed 6 years ago . I spent the last 18 months getting the grip of functional programming, starting with learning OCaml and for some weeks now Haskell.

Global Variables performance effect (c, c++)

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I'm currently developing a very fast algorithm, with one part of it being an extremely fast scanner and statistics function. In this quest, i'm after any performance benefit. Therefore, I'm also interested in keeping the code "multi-thread" friendly. Now for the question : i've noticed that putting some very frequently accessed variables and arrays into "Global", or "static local" (which does the same), there is a measurable performance benefit (in the range of +10%). I'm trying to understand why, and to find a solution about it, since i would prefer to avoid using these types of allocation.

Is my method of measuring running time flawed?

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Sorry, it's a long one, but I'm just explaining my train of thought as I analyze this. Questions at the end. I have an understanding of what goes into measuring running times of code. It's run multiple times to get an average running time to account for differences per run and also to get times when the cache was utilized better. In an attempt to measure running times for someone, I came up with this code after multiple revisions. In the end I ended up with this code which yielded the results I intended to capture without giving misleading numbers: // implementation C static void Test<T>

Why is 2 * x * x faster than 2 * ( x * x ) in Python 3.x, for integers?

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问题 The following Python 3.x integer multiplication takes on average between 1.66s and 1.77s: import time start_time = time.time() num = 0 for x in range(0, 10000000): # num += 2 * (x * x) num += 2 * x * x print("--- %s seconds ---" % (time.time() - start_time)) if I replace 2 * x * x with 2 *(x * x) , it takes between 2.04 and 2.25 . How come? On the other hand it is the opposite in Java: 2 * (x * x) is faster in Java. Java test link: Why is 2 * (i * i) faster than 2 * i * i in Java? I ran each

POSTing multipart/form-data with Apache Bench (ab)

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I'm trying to benchmark our upload server by simulating several concurrent requests using Apache Bench ( ab ). I've read this post that details the necessary steps and also this Stackoverflow question but I'm still unable to create a valid benchmark. This is the command I'm using with Apache Bench ab -n 10 -c 6 -p post_data.txt -T "multipart/form-data; boundary=1234567890" http://myuploadserver.com/upload These are the contents of my post_data.txt file. I apologize for the length. --1234567890 Content-Disposition: form-data; name="upload"; filename="Octocat.png" Content-type: image/png

Which gets the measurements right, JMeter or Apache ab?

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问题 I started writing some basic tests in JMeter and was surprised that the measurements are so different from those from Apache ab. I have a gigabit LAN connecting an Intel i7 server running Nginx and an i5 test machine running JMeter or ab. Initially, I am simply testing the out-of-the box Nginx home page response rate. ab -c 1 -n 100 http://testserver.local/ gives Document Path: / Document Length: 151 bytes Concurrency Level: 1 Time taken for tests: 0.078 seconds Complete requests: 100 Failed