avitevet

#include <mach/mach_time.h>

#include <iostream>

// Shows how to perform accurate performance measurements on modern OS X in application-level code
// on x86 processors.
//
// Performance monitoring on Intel processors is a challenge because the behavior of the internal
// processor counters has changed over the years.  Also, processor frequency used to be fixed,
// but with the introduction of SpeedStep technology the processor frequency may change at

avitevet

#include <algorithm>
#include <iostream>
#include <vector>
#include <cstdio>
#include <cassert>
using namespace std;

typedef double ElementType;
typedef vector<vector<ElementType>> matrix;

avitevet

#include <Windows.h>
#include <iostream>

// Shows how to perform accurate performance measurements on modern Windows in application-level code
// on x86 processors.
//
// Mostly from https://msdn.microsoft.com/en-us/library/windows/desktop/dn553408(v=vs.85).aspx.
// The QueryPerformanceCounter is an abstraction around the processor time-stamp counter, which
// starts at zero when the processor is reset and increments monotonically each cycle.
//

avitevet

Simplex Algorithm Reference Sheet

The simplex algorithm is a method for maximizing or minimizing a linear equation given a set of linear constraints on the variables in the equation.

Definitions

Linear equality

f(x1, x2, .., xn) = b

Linear inequality

avitevet

# val = the value to pad
# length = the length of the padded string
# padChar = the character to use for padding.  Defaults to '0'
pad = (val, length, padChar = '0') ->
  val += ''
  numPads = length - val.length
  if (numPads > 0) then new Array(numPads + 1).join(padChar) + val else val