How do I utilise all the cores for nmake?

c++ eclipse qt multicore nmake

Solution 1

According to MSDN, there's no such option for nmake.

You can however make the compiler build multiple files in parallel by using the /MP option with the VC++ command line compiler and passing multiple files at the same time:

> cl /MP a.cpp b.cpp c.cpp

However note that most Makefiles don't call the compiler like this - they usual invoke the compiler separate for each individual source file, which would prevent the /MP option from doing anything useful.

Solution 2

Another generic, non-Qt-related way to tell nmake to use all the cores is to set environmental variable CL to /MP:

set CL=/MP
nmake

will use all the CPU cores.

Solution 3

QT has a tool for this: http://download.qt.io/official_releases/jom/

They also use it per default in Qt creator.

Solution 4

Incredibuild claims to be able to run nmake builds on multiple cores / multiple machines. I don't have any experience of it.

Solution 5

The CMake 2.8.1 RC1, as for the time of writing this it's ready to try, does bring new generator for NMake which is called NMake Makefiles JOM and it generates NMake with specific settings for jom, which is the drop in replacement of NMake. Thus, it gives multi-processing enabled building using NMake.

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Author by

Furkan Gulsen

Updated on July 09, 2022

Comments

Furkan Gulsen almost 2 years
```
import pandas as pd 
import numpy as np 
import matplotlib.pyplot as plt  d

df = pd.read_csv("coronavirus2_dataset.csv",sep=",") df.head(20)
df.head(20)
```
Here I want to collect the data on the same date and make a new table. How can I achieve this?
- lsterzinger over 4 years
  
  What exactly are you trying to do here? Sum up the "Confirmed", "Deaths", and "Recovered" columns for each date?
- Furkan Gulsen over 4 years
  
  I need to separate the date data. Since there is a lot of data from the same date, I have to collect the dead and dried numbers of the data on the same date and allocate them day by day.
- rrrttt over 4 years
  
  to separate by day we can create a new dataframe like this: df[df.Date == 'date u want']
- AMC over 4 years
  
  Please clarify your question. See: tour, How to Ask, help center.