Introducing the PowerPC SIMD unit

An anonymous reader writes "AltiVec? Velocity Engine? VMX? If you've only been casually following PowerPC development, you might be confused by the various guises of this vector processing SIMD technology. This article covers the basics on what AltiVec is, what it does -- and how it stacks up against its competition."

Comments

The article makes a very good point...

[tabkey12]

This highlights one of the real advantages that AltiVec has over the various SIMD instruction sets available for x86 processors: its comparative stability. Every AltiVec processor since the original G4 has had the same essential functionality, the same large register pool that isn't shared with anything, and a reasonably complete set of likely operations. This has made it easier for support to become widespread: a program designed to take advantage of the original G4 will still get a noticeable performance improvement on today's G5. x86 SIMD was frankly botched - MMX was a very odd idea, and, though SSE & SSE2 have partially fixed the problem, the fact that SSE optimised code usually runs slower on an Athlon than 'unoptimised' code has severely limited its applications.

portable vectorization

[AeiwiMaster]

On the D programing newsgroup we have been talking
about implementing a vectorization syntax, so
we can have portable vector code which
approach the speed of hand coded vectorization.

Here is something from the list.

What is a vectorized expression? Basically, loops that does not specify any
order of execution. If there is no order specified, of course the compiler
can choose any one that is efficient or maybe even distribute the code and
execute it in parallel.

Here is some examples.

Adding a scalar to a vector.
[i in 0..l](a[i]+=0.5)

Finding size of a vector.
size=sqrt(sum([i in 0..l](a[i]*a[i])));

Finding dot-product;
dot=sum([i in 0..l](a[i]*b[i]));

Matrix vector multiplication.
[i in 0..l](r[i]=sum([j in 0..m](a[i,j]*v[j])));

Calculating the trace of a matrix
res=sum([i in 0..l](a[i,i]));

Taylor expansion on every element in a vector
[i in 0..l](r[i]=sum([j in 0..m](a[j]*pow(v[i],j))));

Calculating Fourier series.
f=sum([j in 0..m](a[j]*cos(j*pi*x/2)+b[j]*sin(j*pi*x/2)))+c;

Calculating (A+I)*v using the Kronecker delta-tensor : delta(i,j)={i=j ? 1 : 0}
[i in 0..l](r[i]=sum([j in 0..m]((a[i,j]+delta(i,j))*v[j])));

Calculating cross product of two 3d vectors using the
antisymmetric tensor/Permutation Tensor/Levi-Civita tensor
[i in 0..3](r[i]=sum([j in 0..3,k in 0..3](anti(i,j,k)*a[i]*b[k])));

Calculating determinant of a 4x4 matrix using the antisymmetric tensor
det=sum([i in 0..4,j in 0..4,k in 0..4,l in 0..4]
(anti(i,j,k,l)*a[0,i]*a[1,j]*a[2,k]*a[3,l]) );