Intel(R) Cluster Studio XE 2013 is a powerful tool suite - which helps you to develop applications, with low latency Intel MPI library, high performance C++/FORTRAN compiler, native profiling component named VTune™ Amplifier XE 2013, node level analysis component named Intel® Trace Collector/Analyzer, Threading and memory correctness components named Inspector XE 2013.     

Purposes of this article are: 

One of the pitfalls of parallel programming is the need to consider whether your code modifies a memory location in two parallel strands. Doing so is called a race because whether you get the correct answer depends on the timing of the executed instructions.  Parallel reads are OK, since the value doesn’t change.  But two writes, or a read and a write in parallel are errors. Consider the following code which increments a global location:

Compiler Methodology for Intel® MIC Architecture

Overview

Are you initializing data or copying blocks of data from one variable to another in your application?  Probably so.  Moving or setting blocks of data is very common.  So how to best optimization these operations for Intel(R) Xeon Phi(TM) Coprocessors? 

Problem

Link error with icpc: when linking object files compiled with icpc & g++* along with Boost* MPL library 1.51 or above, as shown in the sample test case below:

%cat t.h
#include <boost/mpl/vector.hpp>
template<typename T> struct my;
void foo(my<boost::mpl::vector<> >* = 0);

%cat u.cpp
#include "t.h"
int main() { foo();}