Counter Strike : Global Offensive Source Code
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//===== Copyright © 1996-2005, Valve Corporation, All rights reserved. ======//
//
// Purpose:
//
//===========================================================================//
#if defined(__SPU__)
#include "platform.h"
#include "basetypes.h"
#include "mathlib/mathlib.h"
#include "mathlib/math_pfns.h"
// #include "mathlib/fltx4.h"
#include "ps3/spu_job_shared.h"
#endif
#include "mathlib/ssemath.h"
#include "mathlib/ssequaternion.h"
#include "mathlib/compressed_vector.h"
// NOTE: This has to be the last file included!
#include "tier0/memdbgon.h"
#if !defined(__SPU__)
const fltx4 Four_PointFives={0.5,0.5,0.5,0.5};
#ifndef _X360
const fltx4 Four_Zeros={0.0,0.0,0.0,0.0};
const fltx4 Four_Ones={1.0,1.0,1.0,1.0};
#endif
const fltx4 Four_Twos={2.0,2.0,2.0,2.0};
const fltx4 Four_Threes={3.0,3.0,3.0,3.0};
const fltx4 Four_Fours={4.0,4.0,4.0,4.0};
const fltx4 Four_Origin={0,0,0,1};
const fltx4 Four_NegativeOnes={-1,-1,-1,-1};
const fltx4 Four_2ToThe21s={ (float) (1<<21), (float) (1<<21), (float) (1<<21), (float)(1<<21) };
const fltx4 Four_2ToThe22s={ (float) (1<<22), (float) (1<<22), (float) (1<<22), (float)(1<<22) };
const fltx4 Four_2ToThe23s={ (float) (1<<23), (float) (1<<23), (float) (1<<23), (float)(1<<23) };
const fltx4 Four_2ToThe24s={ (float) (1<<24), (float) (1<<24), (float) (1<<24), (float)(1<<24) };
const fltx4 Four_Thirds={ 0.33333333, 0.33333333, 0.33333333, 0.33333333 };
const fltx4 Four_TwoThirds={ 0.66666666, 0.66666666, 0.66666666, 0.66666666 };
const fltx4 Four_Point225s={ .225, .225, .225, .225 };
const fltx4 Four_Epsilons={FLT_EPSILON,FLT_EPSILON,FLT_EPSILON,FLT_EPSILON};
const fltx4 Four_DegToRad= { ((float)(M_PI_F / 180.f)), ((float)(M_PI_F / 180.f)), ((float)(M_PI_F / 180.f)), ((float)(M_PI_F / 180.f))};
const fltx4 Four_FLT_MAX={FLT_MAX,FLT_MAX,FLT_MAX,FLT_MAX};
const fltx4 Four_Negative_FLT_MAX={-FLT_MAX,-FLT_MAX,-FLT_MAX,-FLT_MAX};
const fltx4 g_SIMD_0123 = { 0., 1., 2., 3. };
const fltx4 Four_LinearToGammaCoefficients_A = { -3.7295, -3.7295, -3.7295, -3.7295 };
const fltx4 Four_LinearToGammaCoefficients_B = { 8.9635, 8.9635, 8.9635, 8.9635 };
const fltx4 Four_LinearToGammaCoefficients_C = { -7.7397, -7.7397, -7.7397, -7.7397 };
const fltx4 Four_LinearToGammaCoefficients_D = {3.443, 3.443, 3.443, 3.443 };
const fltx4 Four_LinearToGammaCoefficients_E = { 0.048, 0.048, 0.048, 0.048 };
const fltx4 Four_GammaToLinearCoefficients_A = { .1731, .1731, .1731, .1731 };
const fltx4 Four_GammaToLinearCoefficients_B = { .8717, .8717, .8717, .8717 };
const fltx4 Four_GammaToLinearCoefficients_C = { -.0452, -.0452, -.0452, -.0452 };
const fltx4 Four_GammaToLinearCoefficients_D = { .0012, .0012, .0012, .0012 };
const fltx4 g_QuatMultRowSign[4] =
{
{ 1.0f, 1.0f, -1.0f, 1.0f },
{ -1.0f, 1.0f, 1.0f, 1.0f },
{ 1.0f, -1.0f, 1.0f, 1.0f },
{ -1.0f, -1.0f, -1.0f, 1.0f }
};
#endif
const int32 ALIGN16 g_SIMD_clear_signmask[4] ALIGN16_POST = {0x7fffffff,0x7fffffff,0x7fffffff,0x7fffffff};
const int32 ALIGN16 g_SIMD_signmask[4] ALIGN16_POST = { 0x80000000, 0x80000000, 0x80000000, 0x80000000 };
const int32 ALIGN16 g_SIMD_lsbmask[4] ALIGN16_POST = { 0xfffffffe, 0xfffffffe, 0xfffffffe, 0xfffffffe };
const int32 ALIGN16 g_SIMD_clear_wmask[4] ALIGN16_POST = { 0xffffffff, 0xffffffff, 0xffffffff, 0 };
const int32 ALIGN16 g_SIMD_AllOnesMask[4] ALIGN16_POST = { 0xffffffff, 0xffffffff, 0xffffffff, 0xffffffff }; // ~0,~0,~0,~0
const int32 ALIGN16 g_SIMD_Low16BitsMask[4] ALIGN16_POST = { 0xffff, 0xffff, 0xffff, 0xffff }; // 0xffff x 4
const int32 ALIGN16 g_SIMD_ComponentMask[4][4] ALIGN16_POST =
{
{ 0xFFFFFFFF, 0, 0, 0 }, { 0, 0xFFFFFFFF, 0, 0 }, { 0, 0, 0xFFFFFFFF, 0 }, { 0, 0, 0, 0xFFFFFFFF }
};
const fltx4 g_SIMD_Identity[4] =
{
{ 1.0, 0, 0, 0 }, { 0, 1.0, 0, 0 }, { 0, 0, 1.0, 0 }, { 0, 0, 0, 1.0 }
};
const int32 ALIGN16 g_SIMD_SkipTailMask[4][4] ALIGN16_POST =
{
{ 0xffffffff, 0xffffffff, 0xffffffff, 0xffffffff },
{ 0xffffffff, 0x00000000, 0x00000000, 0x00000000 },
{ 0xffffffff, 0xffffffff, 0x00000000, 0x00000000 },
{ 0xffffffff, 0xffffffff, 0xffffffff, 0x00000000 },
};
const int32 ALIGN16 g_SIMD_EveryOtherMask[4] = { 0, ~0, 0, ~0 };
#ifdef PLATFORM_PPC
/// Passed as a parameter to vslh, shuffles the z component of a quat48 stored in the zw words left by one bit.
const uint16 ALIGN16 g_SIMD_Quat48_Unpack_Shift[] = {
0x00, 0x00, // x word
0x00, 0x00, // y word
0x00, 0x01, // z word
0x00, 0x00 }; // w word
// this permutes uint16's x,y,z packed in the most significant four halfwords of a fltx4
// so that each gets its own word in the output. expected use is // __vperm( XX, Four_Threes, permute )
// -- that way each int is represented as 3.0 + n * 2^-22 , which we can pull into the
// appropriate range with a single madd!
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute0[16] =
{
16, 17, 0, 1, // word one: 00XX
16, 17, 2, 3, // word two: 00YY
16, 17, 4, 5, // word three: 00ZZ
16, 17, 6, 7 // word four: 00WW
};
// the other permutes are a little trickier. note: I'm defining them out of order.
// 2 and 5 blend together prior results, rather than a source with 3.0f
// out1 = __vperm( x0y0z0x1y1z1x2y2, Four_Threes, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute1) ); // __x1__y1__z1____
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute1[16] =
{
16, 17, 6, 7, // word one: 00XX
16, 17, 8, 9, // word two: 00YY
16, 17, 10, 11, // word three: 00ZZ
16, 17, 12, 13 // word four: 00WW
};
// out3 = __vperm( z2x3y3z3x4y4z4x5, Four_Threes, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute3) ); // __x3__y3__z3__z2 // z2 is important, goes into out2
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute3[16] =
{
16, 17, 2, 3,
16, 17, 4, 5,
16, 17, 6, 7,
16, 17, 0, 1
};
// out4 = __vperm( z2x3y3z3x4y4z4x5, Four_Threes, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute4) ); // __x4__y4__z4__x5 // x5 is important, goes into out5
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute4[16] =
{
16, 17, 8, 9,
16, 17, 10, 11,
16, 17, 12, 13,
16, 17, 14, 15
};
// out6 = __vperm( y5z5x6y6z6x7y7z7, Four_Threes, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute6) ); // __x6__y6__z6____
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute6[16] =
{
16, 17, 4, 5, // word one
16, 17, 6, 7, // word two
16, 17, 8, 9, // word three
16, 17, 10, 11 // word four (garbage)
};
// out7 = __vperm( y5z5x6y6z6x7y7z7, Four_Threes, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute7) ); // __x7__y7__z7____
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute7[16] =
{
16, 17, 10, 11, // word one
16, 17, 12, 13, // word two
16, 17, 14, 15, // word three
16, 17, 16, 17 // word four (garbage)
};
// these last two are tricky because we mix old output with source input. we get the 3.0f
// from the old output.
// out2 = __vperm( x0y0z0x1y1z1x2y2, out3, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute2) ); // __x2__y2__z2____
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute2[16] =
{
16, 17, 12, 13, // 3.x2
16, 17, 14, 15, // 3.y2
16, 17, 30, 31, // 3.z2 (from out2)
16, 17, 16, 17
};
// out5 = __vperm( y5z5x6y6z6x7y7z7, out4, *reinterpret_cast<const fltx4 *>(g_SIMD_Quat48_Unpack_Permute5) ) // __x5__y5__z5____
const uint8 ALIGN16 g_SIMD_Quat48_Unpack_Permute5[16] =
{
16, 17, 30, 31, // 3.x5 (from out5)
16, 17, 0, 1, // 3.y5
16, 17, 2, 3, // 3.z5
16, 17, 16, 17 // garbage
};
// magic constants that we use to convert the unpacked q48 components from 2 + n * 2^-22 (where n = 0 .. 65535)
// to -1.0 .. 1
#define UnpackMul16s ( (1 << 22) / 32767.5 )
#define UnpackAdd16s ( ( -UnpackMul16s * 3.0 ) - 1 )
// we put the constants all into one word to save a little memory bandwidth
// but otherwise it would look like this:
// static const fltx4 vUpkMul = { UnpackMul16s, UnpackMul16s, UnpackMul16s, UnpackMul16s };
// static const fltx4 vUpkAdd = { UnpackAdd16s , UnpackAdd16s , UnpackAdd16s , UnpackAdd16s };
const fltx4 g_SIMD_Quat48_Unpack_Magic_Constants = { UnpackMul16s , UnpackAdd16s, 0, 0 };
#undef UnpackMul16s
#undef UnpackAdd16s
#endif
// FUNCTIONS
// NOTE: WHY YOU **DO NOT** WANT TO PUT FUNCTIONS HERE
// Generally speaking, you want to make sure SIMD math functions
// are inlined, because that gives the compiler much more latitude
// in instruction scheduling. It's not that the overhead of calling
// the function is particularly great; rather, many of the SIMD
// opcodes have long latencies, and if you have a sequence of
// several dependent ones inside a function call, the latencies
// stack up to create a big penalty. If the function is inlined,
// the compiler can interleave its operations with ones from the
// caller to better hide those latencies. Finally, on the 360,
// putting parameters or return values on the stack, and then
// reading them back within the next forty cycles, is a very
// severe penalty. So, as much as possible, you want to leave your
// data on the registers.
// That said, there are certain occasions where it is appropriate
// to call into functions -- particularly for very large blocks
// of code that will spill most of the registers anyway. Unless your
// function is more than one screen long, yours is probably not one
// of those occasions.
#if !defined(__SPU__)
/// You can use this to rotate a long array of FourVectors all by the same
/// matrix. The first parameter is the head of the array. The second is the
/// number of vectors to rotate. The third is the matrix.
void FourVectors::RotateManyBy(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix )
{
Assert(numVectors > 0);
if ( numVectors == 0 )
return;
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02,
matSplat10, matSplat11, matSplat12,
matSplat20, matSplat21, matSplat22;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the tranpose row of
// the matrix, but we don't really care about that.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
}
#if defined(_X360) || defined(_PS3)
// Same algorithm as above, but the loop is unrolled to eliminate data hazard latencies
// and simplify prefetching. Named variables are deliberately used instead of arrays to
// ensure that the variables live on the registers instead of the stack (stack load/store
// is a serious penalty on 360). Nb: for prefetching to be most efficient here, the
// loop should be unrolled to 8 FourVectors per iteration; because each FourVectors is
// 48 bytes long, 48 * 8 = 384, its least common multiple with the 128-byte cache line.
// That way you can fetch the next 3 cache lines while you work on these three.
// If you do go this route, be sure to dissassemble and make sure it doesn't spill
// registers to stack as you do this; the cost of that will be excessive. Unroll the loop
// a little and just live with the fact that you'll be doing a couple of redundant dbcts
// (they don't cost you anything). Be aware that all three cores share L2 and it can only
// have eight cache lines fetching at a time.
fltx4 outX0, outY0, outZ0; // bank one of outputs
fltx4 outX1, outY1, outZ1; // bank two of outputs
// Because of instruction latencies and scheduling, it's actually faster to use adds and muls
// rather than madds. (Empirically determined by timing.)
const FourVectors * stop = pVectors + numVectors;
FourVectors * RESTRICT pVectNext;
// prime the pump.
if (numVectors & 0x01)
{
// odd number of vectors to process
// prime the 1 group of registers
pVectNext = pVectors++;
outX1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat00 ), MulSIMD( pVectNext->y, matSplat01 ) ), MulSIMD( pVectNext->z, matSplat02 ) );
outY1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat10 ), MulSIMD( pVectNext->y, matSplat11 ) ), MulSIMD( pVectNext->z, matSplat12 ) );
outZ1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat20 ), MulSIMD( pVectNext->y, matSplat21 ) ), MulSIMD( pVectNext->z, matSplat22 ) );
}
else
{
// even number of total vectors to process;
// prime the zero group and jump into the middle of the loop
outX0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ), MulSIMD( pVectors->z, matSplat02 ) );
outY0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ), MulSIMD( pVectors->z, matSplat12 ) );
outZ0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ), MulSIMD( pVectors->z, matSplat22 ) );
goto EVEN_CASE;
}
// perform an even number of iterations through this loop.
while (pVectors < stop)
{
outX0 = MaddSIMD( pVectors->z, matSplat02, AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ) );
outY0 = MaddSIMD( pVectors->z, matSplat12, AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ) );
outZ0 = MaddSIMD( pVectors->z, matSplat22, AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ) );
pVectNext->x = outX1;
pVectNext->y = outY1;
pVectNext->z = outZ1;
EVEN_CASE:
pVectNext = pVectors+1;
outX1 = MaddSIMD( pVectNext->z, matSplat02, AddSIMD( MulSIMD( pVectNext->x, matSplat00 ), MulSIMD( pVectNext->y, matSplat01 ) ) );
outY1 = MaddSIMD( pVectNext->z, matSplat12, AddSIMD( MulSIMD( pVectNext->x, matSplat10 ), MulSIMD( pVectNext->y, matSplat11 ) ) );
outZ1 = MaddSIMD( pVectNext->z, matSplat22, AddSIMD( MulSIMD( pVectNext->x, matSplat20 ), MulSIMD( pVectNext->y, matSplat21 ) ) );
pVectors->x = outX0;
pVectors->y = outY0;
pVectors->z = outZ0;
pVectors += 2;
}
// flush the last round of output
pVectNext->x = outX1;
pVectNext->y = outY1;
pVectNext->z = outZ1;
#else
// PC does not benefit from the unroll/scheduling above
fltx4 outX0, outY0, outZ0; // bank one of outputs
// Because of instruction latencies and scheduling, it's actually faster to use adds and muls
// rather than madds. (Empirically determined by timing.)
const FourVectors * stop = pVectors + numVectors;
// perform an even number of iterations through this loop.
while (pVectors < stop)
{
outX0 = MaddSIMD( pVectors->z, matSplat02, AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ) );
outY0 = MaddSIMD( pVectors->z, matSplat12, AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ) );
outZ0 = MaddSIMD( pVectors->z, matSplat22, AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ) );
pVectors->x = outX0;
pVectors->y = outY0;
pVectors->z = outZ0;
pVectors++;
}
#endif
}
// Get the closest point from P to the (infinite) line through vLineA and vLineB and
// calculate the shortest distance from P to the line.
// If you pass in a value for t, it will tell you the t for (A + (B-A)t) to get the closest point.
// If the closest point lies on the segment between A and B, then 0 <= t <= 1.
void FourVectors::CalcClosestPointOnLineSIMD( const FourVectors &P, const FourVectors &vLineA, const FourVectors &vLineB, FourVectors &vClosest, fltx4 *outT)
{
FourVectors vDir;
fltx4 t = CalcClosestPointToLineTSIMD( P, vLineA, vLineB, vDir );
if ( outT ) *outT = t;
vClosest = vDir;
vClosest *= t;
vClosest += vLineA;
}
fltx4 FourVectors::CalcClosestPointToLineTSIMD( const FourVectors &P, const FourVectors &vLineA, const FourVectors &vLineB, FourVectors &vDir )
{
Assert( s_bMathlibInitialized );
vDir = vLineB;
vDir -= vLineA;
fltx4 div = vDir * vDir;
bi32x4 Mask;
fltx4 Compare = ReplicateX4( 0.00001f );
fltx4 result;
Mask = CmpLtSIMD( div, Compare );
result = DivSIMD( SubSIMD( vDir * P, vDir * vLineA ), div );
MaskedAssign( Mask, Four_Zeros, result );
return result;
}
void FourVectors::RotateManyBy(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix, FourVectors * RESTRICT pOut )
{
Assert(numVectors > 0);
if ( numVectors == 0 )
return;
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02,
matSplat10, matSplat11, matSplat12,
matSplat20, matSplat21, matSplat22;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the tranpose row of
// the matrix, but we don't really care about that.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
}
#if defined(_X360) || defined(_PS3)
// Same algorithm as above, but the loop is unrolled to eliminate data hazard latencies
// and simplify prefetching. Named variables are deliberately used instead of arrays to
// ensure that the variables live on the registers instead of the stack (stack load/store
// is a serious penalty on 360). Nb: for prefetching to be most efficient here, the
// loop should be unrolled to 8 FourVectors per iteration; because each FourVectors is
// 48 bytes long, 48 * 8 = 384, its least common multiple with the 128-byte cache line.
// That way you can fetch the next 3 cache lines while you work on these three.
// If you do go this route, be sure to dissassemble and make sure it doesn't spill
// registers to stack as you do this; the cost of that will be excessive. Unroll the loop
// a little and just live with the fact that you'll be doing a couple of redundant dbcts
// (they don't cost you anything). Be aware that all three cores share L2 and it can only
// have eight cache lines fetching at a time.
fltx4 outX0, outY0, outZ0; // bank one of outputs
fltx4 outX1, outY1, outZ1; // bank two of outputs
// Because of instruction latencies and scheduling, it's actually faster to use adds and muls
// rather than madds. (Empirically determined by timing.)
const FourVectors * stop = pVectors + numVectors;
FourVectors * RESTRICT pVectNext;
FourVectors * RESTRICT pOutNext;
// prime the pump.
if (numVectors & 0x01)
{
// odd number of vectors to process
// prime the 1 group of registers
pVectNext = pVectors++;
pOutNext = pOut++;
outX1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat00 ), MulSIMD( pVectNext->y, matSplat01 ) ), MulSIMD( pVectNext->z, matSplat02 ) );
outY1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat10 ), MulSIMD( pVectNext->y, matSplat11 ) ), MulSIMD( pVectNext->z, matSplat12 ) );
outZ1 = AddSIMD( AddSIMD( MulSIMD( pVectNext->x, matSplat20 ), MulSIMD( pVectNext->y, matSplat21 ) ), MulSIMD( pVectNext->z, matSplat22 ) );
}
else
{
// even number of total vectors to process;
// prime the zero group and jump into the middle of the loop
outX0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ), MulSIMD( pVectors->z, matSplat02 ) );
outY0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ), MulSIMD( pVectors->z, matSplat12 ) );
outZ0 = AddSIMD( AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ), MulSIMD( pVectors->z, matSplat22 ) );
goto EVEN_CASE;
}
// perform an even number of iterations through this loop.
while (pVectors < stop)
{
outX0 = MaddSIMD( pVectors->z, matSplat02, AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ) );
outY0 = MaddSIMD( pVectors->z, matSplat12, AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ) );
outZ0 = MaddSIMD( pVectors->z, matSplat22, AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ) );
pOutNext->x = outX1;
pOutNext->y = outY1;
pOutNext->z = outZ1;
EVEN_CASE:
pVectNext = pVectors+1;
pOutNext = pOut+1;
outX1 = MaddSIMD( pVectNext->z, matSplat02, AddSIMD( MulSIMD( pVectNext->x, matSplat00 ), MulSIMD( pVectNext->y, matSplat01 ) ) );
outY1 = MaddSIMD( pVectNext->z, matSplat12, AddSIMD( MulSIMD( pVectNext->x, matSplat10 ), MulSIMD( pVectNext->y, matSplat11 ) ) );
outZ1 = MaddSIMD( pVectNext->z, matSplat22, AddSIMD( MulSIMD( pVectNext->x, matSplat20 ), MulSIMD( pVectNext->y, matSplat21 ) ) );
pOut->x = outX0;
pOut->y = outY0;
pOut->z = outZ0;
pVectors += 2;
pOut += 2;
}
// flush the last round of output
pVectNext->x = outX1;
pVectNext->y = outY1;
pVectNext->z = outZ1;
#else
// PC does not benefit from the unroll/scheduling above
fltx4 outX0, outY0, outZ0; // bank one of outputs
// Because of instruction latencies and scheduling, it's actually faster to use adds and muls
// rather than madds. (Empirically determined by timing.)
const FourVectors * stop = pVectors + numVectors;
// perform an even number of iterations through this loop.
while (pVectors < stop)
{
outX0 = MaddSIMD( pVectors->z, matSplat02, AddSIMD( MulSIMD( pVectors->x, matSplat00 ), MulSIMD( pVectors->y, matSplat01 ) ) );
outY0 = MaddSIMD( pVectors->z, matSplat12, AddSIMD( MulSIMD( pVectors->x, matSplat10 ), MulSIMD( pVectors->y, matSplat11 ) ) );
outZ0 = MaddSIMD( pVectors->z, matSplat22, AddSIMD( MulSIMD( pVectors->x, matSplat20 ), MulSIMD( pVectors->y, matSplat21 ) ) );
pOut->x = outX0;
pOut->y = outY0;
pOut->z = outZ0;
pVectors++;
pOut++;
}
#endif
}
#ifdef _X360
// Loop-scheduled code to process FourVectors in groups of eight quite efficiently.
void FourVectors_TransformManyGroupsOfEightBy(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix, FourVectors * RESTRICT pOut )
{
Assert(numVectors > 0);
if ( numVectors == 0 )
return;
AssertMsg( (pOut < pVectors && pOut+numVectors <= pVectors) ||
(pOut > pVectors && pVectors+numVectors <= pOut), "FourVectors::TransformManyBy called with overlapping buffer pointers." );
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02, matSplat03, // TWELVE REGISTERS
matSplat10, matSplat11, matSplat12, matSplat13,
matSplat20, matSplat21, matSplat22, matSplat23;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the tranpose row of
// the matrix.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat03 = SplatWSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat13 = SplatWSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
matSplat23 = SplatWSIMD(matCol2);
}
// this macro defines how to compute a specific row from an input and certain splat columns
#define COMPUTE(res, invec, xterm, yterm, zterm, transterm) res = AddSIMD( AddSIMD( MulSIMD((invec)->z, zterm), AddSIMD( MulSIMD( (invec)->x, xterm ), MulSIMD( (invec)->y, yterm ) ) ), transterm )
#define WRITE(term, reg, toptr) toptr->term = reg
// define result groups (we're going to have an eight-way unroll)
fltx4 res0X, res0Y, res0Z, res0XTemp, res0YTemp, res0ZTemp; // 48 REGISTERS
fltx4 res1X, res1Y, res1Z, res1XTemp, res1YTemp, res1ZTemp;
fltx4 res2X, res2Y, res2Z, res2XTemp, res2YTemp, res2ZTemp;
fltx4 res3X, res3Y, res3Z, res3XTemp, res3YTemp, res3ZTemp;
fltx4 res4X, res4Y, res4Z, res4XTemp, res4YTemp, res4ZTemp;
fltx4 res5X, res5Y, res5Z, res5XTemp, res5YTemp, res5ZTemp;
fltx4 res6X, res6Y, res6Z, res6XTemp, res6YTemp, res6ZTemp;
fltx4 res7X, res7Y, res7Z, res7XTemp, res7YTemp, res7ZTemp;
// #define FROZ(out,in,offset) COMPUTE((out+offset)->x, (in + offset), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE((out + offset )->y, (in + offset), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE((out + offset)->z, (in + offset), matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_GROUP(resgroup,dataptr) COMPUTE(resgroup ## X, (dataptr), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE(resgroup ## Y, (dataptr), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE(resgroup ## Z, (dataptr), matSplat20, matSplat21, matSplat22, matSplat23)
#define WRITE_GROUP(ptr, resgroup) (ptr)->x = resgroup ## X; (ptr)->y = resgroup ## Y; (ptr)->z = resgroup ## Z
/*
// stage 1 -- 6 ops for xyz, each w 12 cycle latency
res0X = MulSIMD( (invec)->y, matSplat01 );
res0Temp = MaddSIMD((invec)->z, matSplat02, matSplat03);
// stage 2 -- 3 clocks for xyz
res0X = MaddSIMD( (invec)->x, matSplat00, res0X );
// stage 3 -- 3 clocks for xyz
res0X = AddSIMD(res0X, res0Temp);
*/
#define COMPUTE_STAGE1_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MulSIMD( (invec)->y, ysplat ); tempvar = MaddSIMD((invec)->z, zsplat, transplat)
#define COMPUTE_STAGE2_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MaddSIMD( (invec)->x, xsplat, res )
#define COMPUTE_STAGE3_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = AddSIMD(res, tempvar) // frees up the tempvar
#define COMPUTE_STAGE1_GROUP(resgroup, invec) COMPUTE_STAGE1_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE1_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE1_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE2_GROUP(resgroup, invec) COMPUTE_STAGE2_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE2_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE2_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE3_GROUP(resgroup, invec) COMPUTE_STAGE3_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE3_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE3_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
FourVectors * RESTRICT inData = pVectors;
FourVectors * RESTRICT outData = pOut;
const FourVectors * const RESTRICT STOP = pVectors + numVectors;
// Use techniques of loop scheduling to eliminate data hazards; process
// eight groups simultaneously so that we never have any operations stalling
// waiting for data.
// Note: this loop, while pretty fast, could be faster still -- you'll notice
// that it does all of its loads, then all computation, then writes everything
// out. If made truly cyclic, such that every line interleaved a stage 1, stage 2,
// stage 3, and write, then throughput could be higher (probably by about 50%).
while (inData < STOP)
{
// start prefetching the three cache lines
// we'll hit two iterations from now
__dcbt( sizeof(FourVectors) * 16, inData );
__dcbt( sizeof(FourVectors) * 16 + 128, inData );
__dcbt( sizeof(FourVectors) * 16 + 256, inData );
// synchro
COMPUTE_STAGE1_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res3, inData + 3);
COMPUTE_STAGE2_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res4, inData + 4);
COMPUTE_STAGE2_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res5, inData + 5);
COMPUTE_STAGE2_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res6, inData + 6);
COMPUTE_STAGE2_GROUP(res3, inData + 3);
COMPUTE_STAGE1_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res0, inData + 0);
COMPUTE_STAGE2_GROUP(res4, inData + 4);
COMPUTE_STAGE3_GROUP(res1, inData + 1);
COMPUTE_STAGE2_GROUP(res5, inData + 5);
COMPUTE_STAGE3_GROUP(res2, inData + 2);
COMPUTE_STAGE2_GROUP(res6, inData + 6);
COMPUTE_STAGE3_GROUP(res3, inData + 3);
COMPUTE_STAGE2_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res4, inData + 4);
WRITE_GROUP( outData + 0, res0 );
COMPUTE_STAGE3_GROUP(res5, inData + 5);
WRITE_GROUP( outData + 1, res1 );
COMPUTE_STAGE3_GROUP(res6, inData + 6);
WRITE_GROUP( outData + 2, res2 );
COMPUTE_STAGE3_GROUP(res7, inData + 7);
WRITE_GROUP( outData + 3, res3 );
WRITE_GROUP( outData + 4, res4 );
WRITE_GROUP( outData + 5, res5 );
WRITE_GROUP( outData + 6, res6 );
WRITE_GROUP( outData + 7, res7 );
inData += 8;
outData += 8;
}
#undef COMPUTE
#undef WRITE
#undef COMPUTE_STAGE1_ROW
#undef COMPUTE_STAGE2_ROW
#undef COMPUTE_STAGE3_ROW
#undef COMPUTE_STAGE1_GROUP
#undef COMPUTE_STAGE2_GROUP
#undef COMPUTE_STAGE3_GROUP
#undef COMPUTE_GROUP
#undef WRITE_GROUP
}
#ifdef _X360
// Loop-scheduled code to process FourVectors in groups of eight quite efficiently. This is the version
// to call when starting on a 128-byte-aligned address.
void FourVectors_TransformManyGroupsOfEightBy_128byteAligned(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix, FourVectors * RESTRICT pOut )
{
/* If this has changed, you will need to change all the prefetches, *
* and groups of eight are no longer the ideal unit for iterating *
* on many vectors. */
COMPILE_TIME_ASSERT( sizeof(FourVectors) == 48 ) ;
Assert(numVectors > 0);
if ( numVectors == 0 )
return;
AssertMsg((numVectors & 0x07) == 0, "FourVectors_TransformManyGroupsOfEight called with numVectors % 8 != 0!");
// Assert alignment
AssertMsg( ( ( reinterpret_cast<uint32>( pVectors ) & 127 ) == 0) &&
( ( reinterpret_cast<uint32>(pOut) & 127 ) == 0),
"FourVectors_Transform..aligned called with non-128-byte-aligned buffers." );
// Assert non overlap
AssertMsg( (pOut < pVectors && pOut+numVectors <= pVectors) ||
(pOut > pVectors && pVectors+numVectors <= pOut), "FourVectors::TransformManyBy called with overlapping buffer pointers." );
// Here's the plan. 8 four-vecs = 3 cache lines exactly. It takes about 400 cycles to process a group
// of eight, and cache latency is 600 cycles, so we try to prefetch two iterations ahead (eg fetch
// iteration 3 while working on iteration 1). In the case of the output, we can simply zero-flush
// the cache lines since we are sure to write into them. Because we're reading and fetching two ahead,
// we want to stop two away from the last iteration.
// No matter what, we will need to prefetch the first two groups of eight of input (that's the
// first six cache lines)
__dcbt( 0, pVectors );
__dcbt( 128, pVectors );
__dcbt( 256, pVectors );
__dcbt( 384, pVectors );
__dcbt( 512, pVectors );
__dcbt( 640, pVectors );
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02, matSplat03, // TWELVE REGISTERS
matSplat10, matSplat11, matSplat12, matSplat13,
matSplat20, matSplat21, matSplat22, matSplat23;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the tranpose row of
// the matrix.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat03 = SplatWSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat13 = SplatWSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
matSplat23 = SplatWSIMD(matCol2);
}
// this macro defines how to compute a specific row from an input and certain splat columns
#define COMPUTE(res, invec, xterm, yterm, zterm, transterm) res = AddSIMD( AddSIMD( MulSIMD((invec)->z, zterm), AddSIMD( MulSIMD( (invec)->x, xterm ), MulSIMD( (invec)->y, yterm ) ) ), transterm )
#define WRITE(term, reg, toptr) toptr->term = reg
// define result groups (we're going to have an eight-way unroll)
fltx4 res0X, res0Y, res0Z, res0XTemp, res0YTemp, res0ZTemp; // 48 REGISTERS
fltx4 res1X, res1Y, res1Z, res1XTemp, res1YTemp, res1ZTemp;
fltx4 res2X, res2Y, res2Z, res2XTemp, res2YTemp, res2ZTemp;
fltx4 res3X, res3Y, res3Z, res3XTemp, res3YTemp, res3ZTemp;
fltx4 res4X, res4Y, res4Z, res4XTemp, res4YTemp, res4ZTemp;
fltx4 res5X, res5Y, res5Z, res5XTemp, res5YTemp, res5ZTemp;
fltx4 res6X, res6Y, res6Z, res6XTemp, res6YTemp, res6ZTemp;
fltx4 res7X, res7Y, res7Z, res7XTemp, res7YTemp, res7ZTemp;
// #define FROZ(out,in,offset) COMPUTE((out+offset)->x, (in + offset), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE((out + offset )->y, (in + offset), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE((out + offset)->z, (in + offset), matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_GROUP(resgroup,dataptr) COMPUTE(resgroup ## X, (dataptr), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE(resgroup ## Y, (dataptr), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE(resgroup ## Z, (dataptr), matSplat20, matSplat21, matSplat22, matSplat23)
#define WRITE_GROUP(ptr, resgroup) (ptr)->x = resgroup ## X; (ptr)->y = resgroup ## Y; (ptr)->z = resgroup ## Z
/*
// stage 1 -- 6 ops for xyz, each w 12 cycle latency
res0X = MulSIMD( (invec)->y, matSplat01 );
res0Temp = MaddSIMD((invec)->z, matSplat02, matSplat03);
// stage 2 -- 3 clocks for xyz
res0X = MaddSIMD( (invec)->x, matSplat00, res0X );
// stage 3 -- 3 clocks for xyz
res0X = AddSIMD(res0X, res0Temp);
*/
#define COMPUTE_STAGE1_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MulSIMD( (invec)->y, ysplat ); tempvar = MaddSIMD((invec)->z, zsplat, transplat)
#define COMPUTE_STAGE2_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MaddSIMD( (invec)->x, xsplat, res )
#define COMPUTE_STAGE3_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = AddSIMD(res, tempvar) // frees up the tempvar
#define COMPUTE_STAGE1_GROUP(resgroup, invec) COMPUTE_STAGE1_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE1_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE1_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE2_GROUP(resgroup, invec) COMPUTE_STAGE2_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE2_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE2_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE3_GROUP(resgroup, invec) COMPUTE_STAGE3_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE3_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE3_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
// Okay. First do all but the last two turns of the crank; we don't want to overshoot with the flush-to-zero.
FourVectors * RESTRICT inData = pVectors;
FourVectors * RESTRICT outData = pOut;
const FourVectors * RESTRICT STOP;
if (numVectors > 16)
{
STOP = pVectors + numVectors - 16;
// flush the first two blocks we'll write into
__dcbz128( 0, outData );
__dcbz128( 128, outData );
__dcbz128( 256, outData );
while (inData < STOP)
{
// start prefetching the three cache lines
// we'll hit two iterations from now
__dcbt( sizeof(FourVectors) * 16, inData );
__dcbt( sizeof(FourVectors) * 16 + 128, inData );
__dcbt( sizeof(FourVectors) * 16 + 256, inData );
// synchro
COMPUTE_STAGE1_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res3, inData + 3);
// pre-zero the three cache lines we'll overwrite
// in the next iteration
__dcbz128( 384, outData );
__dcbz128( 512, outData );
__dcbz128( 640, outData );
COMPUTE_STAGE2_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res4, inData + 4);
COMPUTE_STAGE2_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res5, inData + 5);
COMPUTE_STAGE2_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res6, inData + 6);
COMPUTE_STAGE2_GROUP(res3, inData + 3);
COMPUTE_STAGE1_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res0, inData + 0);
COMPUTE_STAGE2_GROUP(res4, inData + 4);
COMPUTE_STAGE3_GROUP(res1, inData + 1);
COMPUTE_STAGE2_GROUP(res5, inData + 5);
COMPUTE_STAGE3_GROUP(res2, inData + 2);
COMPUTE_STAGE2_GROUP(res6, inData + 6);
COMPUTE_STAGE3_GROUP(res3, inData + 3);
COMPUTE_STAGE2_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res4, inData + 4);
WRITE_GROUP( outData + 0, res0 );
COMPUTE_STAGE3_GROUP(res5, inData + 5);
WRITE_GROUP( outData + 1, res1 );
COMPUTE_STAGE3_GROUP(res6, inData + 6);
WRITE_GROUP( outData + 2, res2 );
COMPUTE_STAGE3_GROUP(res7, inData + 7);
WRITE_GROUP( outData + 3, res3 );
WRITE_GROUP( outData + 4, res4 );
WRITE_GROUP( outData + 5, res5 );
WRITE_GROUP( outData + 6, res6 );
WRITE_GROUP( outData + 7, res7 );
inData += 8;
outData += 8;
}
}
else if (numVectors == 16)
{
// zero out the exactly six cache lines we will write into
__dcbz128( 0, outData );
__dcbz128( 128, outData );
__dcbz128( 256, outData );
__dcbz128( 384, outData );
__dcbz128( 512, outData );
__dcbz128( 640, outData );
}
else if (numVectors == 8)
{
// zero out the exactly three cache lines we will write into
__dcbz128( 0, outData );
__dcbz128( 128, outData );
__dcbz128( 256, outData );
}
else
{
AssertMsg(false, "Can't happen!");
}
// deal with the ultimate two groups (or, if we were fed
// less than 16 groups, the whole shebang)
STOP = pVectors + numVectors - 16;
// Use techniques of loop scheduling to eliminate data hazards; process
// eight groups simultaneously so that we never have any operations stalling
// waiting for data.
// Note: this loop, while pretty fast, could be faster still -- you'll notice
// that it does all of its loads, then all computation, then writes everything
// out. If made truly cyclic, such that every line interleaved a stage 1, stage 2,
// stage 3, and write, then throughput could be higher (probably by about 50%).
while (inData < STOP)
{
// synchro
COMPUTE_STAGE1_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res3, inData + 3);
COMPUTE_STAGE2_GROUP(res0, inData + 0);
COMPUTE_STAGE1_GROUP(res4, inData + 4);
COMPUTE_STAGE2_GROUP(res1, inData + 1);
COMPUTE_STAGE1_GROUP(res5, inData + 5);
COMPUTE_STAGE2_GROUP(res2, inData + 2);
COMPUTE_STAGE1_GROUP(res6, inData + 6);
COMPUTE_STAGE2_GROUP(res3, inData + 3);
COMPUTE_STAGE1_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res0, inData + 0);
COMPUTE_STAGE2_GROUP(res4, inData + 4);
COMPUTE_STAGE3_GROUP(res1, inData + 1);
COMPUTE_STAGE2_GROUP(res5, inData + 5);
COMPUTE_STAGE3_GROUP(res2, inData + 2);
COMPUTE_STAGE2_GROUP(res6, inData + 6);
COMPUTE_STAGE3_GROUP(res3, inData + 3);
COMPUTE_STAGE2_GROUP(res7, inData + 7);
COMPUTE_STAGE3_GROUP(res4, inData + 4);
WRITE_GROUP( outData + 0, res0 );
COMPUTE_STAGE3_GROUP(res5, inData + 5);
WRITE_GROUP( outData + 1, res1 );
COMPUTE_STAGE3_GROUP(res6, inData + 6);
WRITE_GROUP( outData + 2, res2 );
COMPUTE_STAGE3_GROUP(res7, inData + 7);
WRITE_GROUP( outData + 3, res3 );
WRITE_GROUP( outData + 4, res4 );
WRITE_GROUP( outData + 5, res5 );
WRITE_GROUP( outData + 6, res6 );
WRITE_GROUP( outData + 7, res7 );
inData += 8;
outData += 8;
}
#undef COMPUTE
#undef WRITE
#undef COMPUTE_STAGE1_ROW
#undef COMPUTE_STAGE2_ROW
#undef COMPUTE_STAGE3_ROW
#undef COMPUTE_STAGE1_GROUP
#undef COMPUTE_STAGE2_GROUP
#undef COMPUTE_STAGE3_GROUP
#undef COMPUTE_GROUP
#undef WRITE_GROUP
}
#endif
// Transform a long array of FourVectors by a given matrix.
void FourVectors::TransformManyBy(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix, FourVectors * RESTRICT pOut )
{
Assert(numVectors > 0);
AssertMsg( (pOut < pVectors && pOut+numVectors <= pVectors) ||
(pOut > pVectors && pVectors+numVectors <= pOut), "FourVectors::TransformManyBy called with overlapping buffer pointers." );
#ifdef _X360
// The really fast version of this function likes to operate on blocks of eight. So, chug through
// groups of eight, then deal with any leftovers.
int numVectorsRoundedToNearestEight = numVectors & (~0x07);
if (numVectors >= 8)
{
// aligned?
if ((reinterpret_cast<unsigned int>(pVectors) & 127) == 0 && (reinterpret_cast<unsigned int>(pOut) & 127) == 0)
{
FourVectors_TransformManyGroupsOfEightBy_128byteAligned(pVectors, numVectorsRoundedToNearestEight, rotationMatrix, pOut);
}
else
{
FourVectors_TransformManyGroupsOfEightBy(pVectors, numVectorsRoundedToNearestEight, rotationMatrix, pOut);
}
numVectors -= numVectorsRoundedToNearestEight;
pVectors += numVectorsRoundedToNearestEight;
pOut += numVectorsRoundedToNearestEight;
}
#endif
// any left over?
if (numVectors > 0)
{
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02, matSplat03, // TWELVE REGISTERS
matSplat10, matSplat11, matSplat12, matSplat13,
matSplat20, matSplat21, matSplat22, matSplat23;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the transpose row of
// the matrix.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat03 = SplatWSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat13 = SplatWSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
matSplat23 = SplatWSIMD(matCol2);
}
do
{
// Trust in the compiler to schedule these operations correctly:
pOut->x = MaddSIMD(pVectors->z, matSplat02, MaddSIMD(pVectors->y, matSplat01, MaddSIMD(pVectors->x, matSplat00, matSplat03)));
pOut->y = MaddSIMD(pVectors->z, matSplat12, MaddSIMD(pVectors->y, matSplat11, MaddSIMD(pVectors->x, matSplat00, matSplat13)));
pOut->z = MaddSIMD(pVectors->z, matSplat22, MaddSIMD(pVectors->y, matSplat21, MaddSIMD(pVectors->x, matSplat00, matSplat23)));
++pOut;
++pVectors;
--numVectors;
} while(numVectors > 0);
}
}
#ifdef _X360
// Loop-scheduled code to process FourVectors in groups of eight quite efficiently.
static void FourVectors_TransformManyGroupsOfEightBy_InPlace(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix )
{
Assert(numVectors > 0);
if ( numVectors == 0 )
return;
// Prefetch line 1 and 2
__dcbt(0,pVectors);
__dcbt(128,pVectors);
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02, matSplat03, // TWELVE REGISTERS
matSplat10, matSplat11, matSplat12, matSplat13,
matSplat20, matSplat21, matSplat22, matSplat23;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the tranpose row of
// the matrix.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat03 = SplatWSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat13 = SplatWSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
matSplat23 = SplatWSIMD(matCol2);
}
// this macro defines how to compute a specific row from an input and certain splat columns
#define COMPUTE(res, invec, xterm, yterm, zterm, transterm) res = AddSIMD( AddSIMD( MulSIMD((invec)->z, zterm), AddSIMD( MulSIMD( (invec)->x, xterm ), MulSIMD( (invec)->y, yterm ) ) ), transterm )
#define WRITE(term, reg, toptr) toptr->term = reg
// define result groups (we're going to have an eight-way unroll)
fltx4 res0X, res0Y, res0Z, res0XTemp, res0YTemp, res0ZTemp; // 48 REGISTERS
fltx4 res1X, res1Y, res1Z, res1XTemp, res1YTemp, res1ZTemp;
fltx4 res2X, res2Y, res2Z, res2XTemp, res2YTemp, res2ZTemp;
fltx4 res3X, res3Y, res3Z, res3XTemp, res3YTemp, res3ZTemp;
fltx4 res4X, res4Y, res4Z, res4XTemp, res4YTemp, res4ZTemp;
fltx4 res5X, res5Y, res5Z, res5XTemp, res5YTemp, res5ZTemp;
fltx4 res6X, res6Y, res6Z, res6XTemp, res6YTemp, res6ZTemp;
fltx4 res7X, res7Y, res7Z, res7XTemp, res7YTemp, res7ZTemp;
// #define FROZ(out,in,offset) COMPUTE((out+offset)->x, (in + offset), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE((out + offset )->y, (in + offset), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE((out + offset)->z, (in + offset), matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_GROUP(resgroup,dataptr) COMPUTE(resgroup ## X, (dataptr), matSplat00, matSplat01, matSplat02, matSplat03); COMPUTE(resgroup ## Y, (dataptr), matSplat10, matSplat11, matSplat12, matSplat13); COMPUTE(resgroup ## Z, (dataptr), matSplat20, matSplat21, matSplat22, matSplat23)
#define WRITE_GROUP(ptr, resgroup) (ptr)->x = resgroup ## X; (ptr)->y = resgroup ## Y; (ptr)->z = resgroup ## Z
/*
// stage 1 -- 6 ops for xyz, each w 12 cycle latency
res0X = MulSIMD( (invec)->y, matSplat01 );
res0Temp = MaddSIMD((invec)->z, matSplat02, matSplat03);
// stage 2 -- 3 clocks for xyz
res0X = MaddSIMD( (invec)->x, matSplat00, res0X );
// stage 3 -- 3 clocks for xyz
res0X = AddSIMD(res0X, res0Temp);
*/
#define COMPUTE_STAGE1_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MulSIMD( (invec)->y, ysplat ); tempvar = MaddSIMD((invec)->z, zsplat, transplat)
#define COMPUTE_STAGE2_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = MaddSIMD( (invec)->x, xsplat, res )
#define COMPUTE_STAGE3_ROW(res, tempvar, invec, xsplat, ysplat, zsplat, transplat) res = AddSIMD(res, tempvar) // frees up the tempvar
#define COMPUTE_STAGE1_GROUP(resgroup, invec) COMPUTE_STAGE1_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE1_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE1_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE2_GROUP(resgroup, invec) COMPUTE_STAGE2_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE2_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE2_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
#define COMPUTE_STAGE3_GROUP(resgroup, invec) COMPUTE_STAGE3_ROW(resgroup ## X, resgroup ## X ## Temp, invec, matSplat00, matSplat01, matSplat02, matSplat03);\
COMPUTE_STAGE3_ROW(resgroup ## Y, resgroup ## Y ## Temp, invec, matSplat10, matSplat11, matSplat12, matSplat13);\
COMPUTE_STAGE3_ROW(resgroup ## Z, resgroup ## Z ## Temp, invec, matSplat20, matSplat21, matSplat22, matSplat23)
const FourVectors * const RESTRICT STOP = pVectors + numVectors;
// Use techniques of loop scheduling to eliminate data hazards; process
// eight groups simultaneously so that we never have any operations stalling
// waiting for data.
// Note: this loop, while pretty fast, could be faster still -- you'll notice
// that it does all of its loads, then all computation, then writes everything
// out. If made truly cyclic, such that every line interleaved a stage 1, stage 2,
// stage 3, and write, then throughput could be higher (probably by about 50%).
while (pVectors < STOP)
{
// start prefetching the three cache lines
// we'll hit two iterations from now
__dcbt( sizeof(FourVectors) * 16, pVectors );
__dcbt( sizeof(FourVectors) * 16 + 128, pVectors );
__dcbt( sizeof(FourVectors) * 16 + 256, pVectors );
// synchro
COMPUTE_STAGE1_GROUP(res0, pVectors + 0);
COMPUTE_STAGE1_GROUP(res1, pVectors + 1);
COMPUTE_STAGE1_GROUP(res2, pVectors + 2);
COMPUTE_STAGE1_GROUP(res3, pVectors + 3);
COMPUTE_STAGE2_GROUP(res0, pVectors + 0);
COMPUTE_STAGE1_GROUP(res4, pVectors + 4);
COMPUTE_STAGE2_GROUP(res1, pVectors + 1);
COMPUTE_STAGE1_GROUP(res5, pVectors + 5);
COMPUTE_STAGE2_GROUP(res2, pVectors + 2);
COMPUTE_STAGE1_GROUP(res6, pVectors + 6);
COMPUTE_STAGE2_GROUP(res3, pVectors + 3);
COMPUTE_STAGE1_GROUP(res7, pVectors + 7);
COMPUTE_STAGE3_GROUP(res0, pVectors + 0);
COMPUTE_STAGE2_GROUP(res4, pVectors + 4);
COMPUTE_STAGE3_GROUP(res1, pVectors + 1);
COMPUTE_STAGE2_GROUP(res5, pVectors + 5);
COMPUTE_STAGE3_GROUP(res2, pVectors + 2);
COMPUTE_STAGE2_GROUP(res6, pVectors + 6);
COMPUTE_STAGE3_GROUP(res3, pVectors + 3);
COMPUTE_STAGE2_GROUP(res7, pVectors + 7);
COMPUTE_STAGE3_GROUP(res4, pVectors + 4);
WRITE_GROUP( pVectors + 0, res0 );
COMPUTE_STAGE3_GROUP(res5, pVectors + 5);
WRITE_GROUP( pVectors + 1, res1 );
COMPUTE_STAGE3_GROUP(res6, pVectors + 6);
WRITE_GROUP( pVectors + 2, res2 );
COMPUTE_STAGE3_GROUP(res7, pVectors + 7);
WRITE_GROUP( pVectors + 3, res3 );
WRITE_GROUP( pVectors + 4, res4 );
WRITE_GROUP( pVectors + 5, res5 );
WRITE_GROUP( pVectors + 6, res6 );
WRITE_GROUP( pVectors + 7, res7 );
pVectors += 8;
}
#undef COMPUTE
#undef WRITE
#undef COMPUTE_STAGE1_ROW
#undef COMPUTE_STAGE2_ROW
#undef COMPUTE_STAGE3_ROW
#undef COMPUTE_STAGE1_GROUP
#undef COMPUTE_STAGE2_GROUP
#undef COMPUTE_STAGE3_GROUP
#undef COMPUTE_GROUP
#undef WRITE_GROUP
}
#endif
// In-place version of above. It's necessary to have this, rather than just allowing pOut and pVectors
// to equal each other, because of the semantics of RESTRICT: pVectors and pOut must not be allowed
// to alias. (Simply un-restricting the pointers results in very poor scheduling.)
void FourVectors::TransformManyBy(FourVectors * RESTRICT pVectors, unsigned int numVectors, const matrix3x4_t& rotationMatrix )
{
Assert(numVectors > 0);
#ifdef _X360
// The really fast version of this function likes to operate on blocks of eight. So, chug through
// groups of eight, then deal with any leftovers.
int numVectorsRoundedToNearestEight = numVectors & (~0x07);
if (numVectors >= 8)
{
FourVectors_TransformManyGroupsOfEightBy_InPlace(pVectors, numVectorsRoundedToNearestEight, rotationMatrix);
numVectors -= numVectorsRoundedToNearestEight;
pVectors += numVectorsRoundedToNearestEight;
}
#endif
// any left over?
if (numVectors > 0)
{
// Splat out each of the entries in the matrix to a fltx4. Do this
// in the order that we will need them, to hide latency. I'm
// avoiding making an array of them, so that they'll remain in
// registers.
fltx4 matSplat00, matSplat01, matSplat02, matSplat03, // TWELVE REGISTERS
matSplat10, matSplat11, matSplat12, matSplat13,
matSplat20, matSplat21, matSplat22, matSplat23;
{
// Load the matrix into local vectors. Sadly, matrix3x4_ts are
// often unaligned. The w components will be the transpose row of
// the matrix.
fltx4 matCol0 = LoadUnalignedSIMD(rotationMatrix[0]);
fltx4 matCol1 = LoadUnalignedSIMD(rotationMatrix[1]);
fltx4 matCol2 = LoadUnalignedSIMD(rotationMatrix[2]);
matSplat00 = SplatXSIMD(matCol0);
matSplat01 = SplatYSIMD(matCol0);
matSplat02 = SplatZSIMD(matCol0);
matSplat03 = SplatWSIMD(matCol0);
matSplat10 = SplatXSIMD(matCol1);
matSplat11 = SplatYSIMD(matCol1);
matSplat12 = SplatZSIMD(matCol1);
matSplat13 = SplatWSIMD(matCol1);
matSplat20 = SplatXSIMD(matCol2);
matSplat21 = SplatYSIMD(matCol2);
matSplat22 = SplatZSIMD(matCol2);
matSplat23 = SplatWSIMD(matCol2);
}
do
{
fltx4 resultX, resultY, resultZ;
// Trust in the compiler to schedule these operations correctly:
resultX = MaddSIMD(pVectors->z, matSplat02, MaddSIMD(pVectors->y, matSplat01, MaddSIMD(pVectors->x, matSplat00, matSplat03)));
resultY = MaddSIMD(pVectors->z, matSplat12, MaddSIMD(pVectors->y, matSplat11, MaddSIMD(pVectors->x, matSplat00, matSplat13)));
resultZ = MaddSIMD(pVectors->z, matSplat22, MaddSIMD(pVectors->y, matSplat21, MaddSIMD(pVectors->x, matSplat00, matSplat23)));
pVectors->x = resultX;
pVectors->y = resultY;
pVectors->z = resultZ;
++pVectors;
--numVectors;
} while(numVectors > 0);
}
}
#endif
// Transform many (horizontal) points in-place by a 3x4 matrix,
// here already loaded onto three fltx4 registers but not transposed.
// The points must be stored as 16-byte aligned. They are points
// and not vectors because we assume the w-component to be 1.
#ifdef _X360
void TransformManyPointsBy(VectorAligned * RESTRICT pVectors, unsigned int numVectors, FLTX4 mRow0, FLTX4 mRow1, FLTX4 mRow2)
{
/**************************************************
* Here is an elaborate and carefully scheduled *
* algorithm nicked from xboxmath.inl and hacked *
* up for 3x4 matrices. *
**************************************************/
COMPILE_TIME_ASSERT(sizeof(VectorAligned) == sizeof(XMFLOAT4)); // VectorAligned's need to be 16 bytes
XMVECTOR R0[8], R1[8], R2[8];
XMVECTOR vIn[8];
// C_ASSERT(UnrollCount == 8);
// C_ASSERT(sizeof(XMFLOAT4) == 16);
Assert(pVectors);
Assert(((UINT_PTR)pVectors & 3) == 0); // assert alignment
UINT GroupIndex;
VectorAligned * RESTRICT vCurrent = pVectors;
// sentinel pointers
VectorAligned * vStreamEnd, *vStreamGroupBase, *vStreamGroupEnd;
{
// cook up the pointers from integer math. Necessary because otherwise we LHS all over
// the place. (Odd that this doesn't happen to the xbox math.)
UINT_PTR InputVector = (UINT_PTR)pVectors;
UINT_PTR InputStreamEnd = InputVector + numVectors * sizeof(XMFLOAT4);
// compute start and end points on 128-byte alignment
UINT_PTR InputStreamCGroupBase = XMMin(InputVector + (XM_CACHE_LINE_SIZE - 1), InputStreamEnd) & ~(XM_CACHE_LINE_SIZE - 1);
UINT_PTR InputStreamCGroupEnd = InputStreamCGroupBase + ((InputStreamEnd - InputStreamCGroupBase) & ~(4 * XM_CACHE_LINE_SIZE - 1));
vStreamEnd = (VectorAligned *)InputStreamEnd;
vStreamGroupBase = (VectorAligned *)InputStreamCGroupBase;
vStreamGroupEnd = (VectorAligned *)InputStreamCGroupEnd;
}
__dcbt(0, vStreamGroupBase);
__dcbt(XM_CACHE_LINE_SIZE, vStreamGroupBase);
__dcbt(XM_CACHE_LINE_SIZE * 2, vStreamGroupBase);
__dcbt(XM_CACHE_LINE_SIZE * 3, vStreamGroupBase);
while (vCurrent < vStreamGroupBase)
{
fltx4 vec = __lvx(vCurrent->Base(), 0);
R0[0] = __vmsum4fp(vec, mRow0);
R1[0] = __vmsum4fp(vec, mRow1);
R2[0] = __vmsum4fp(vec, mRow2);
__stvewx(R0[0], vCurrent->Base(), 0);
__stvewx(R1[0], vCurrent->Base(), 4);
__stvewx(R2[0], vCurrent->Base(), 8);
vCurrent++;
}
while (vCurrent < vStreamGroupEnd)
{
__dcbt(XM_CACHE_LINE_SIZE * 4, vCurrent);
__dcbt(XM_CACHE_LINE_SIZE * 5, vCurrent);
__dcbt(XM_CACHE_LINE_SIZE * 6, vCurrent);
__dcbt(XM_CACHE_LINE_SIZE * 7, vCurrent);
for (GroupIndex = 0; GroupIndex < 4; GroupIndex++)
{
// all kinds of LHS on this pointer. Why?
VectorAligned* OutputVector = vCurrent;
vIn[0] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[1] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[2] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[3] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[4] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[5] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[6] = __lvx(vCurrent->Base(), 0);
vCurrent++;
vIn[7] = __lvx(vCurrent->Base(), 0);
vCurrent++;
R0[0] = __vmsum4fp(vIn[0], mRow0);
R1[0] = __vmsum4fp(vIn[0], mRow1);
R2[0] = __vmsum4fp(vIn[0], mRow2);
R0[1] = __vmsum4fp(vIn[1], mRow0);
R1[1] = __vmsum4fp(vIn[1], mRow1);
R2[1] = __vmsum4fp(vIn[1], mRow2);
R0[2] = __vmsum4fp(vIn[2], mRow0);
R1[2] = __vmsum4fp(vIn[2], mRow1);
R2[2] = __vmsum4fp(vIn[2], mRow2);
R0[3] = __vmsum4fp(vIn[3], mRow0);
R1[3] = __vmsum4fp(vIn[3], mRow1);
R2[3] = __vmsum4fp(vIn[3], mRow2);
R0[4] = __vmsum4fp(vIn[4], mRow0);
R1[4] = __vmsum4fp(vIn[4], mRow1);
R2[4] = __vmsum4fp(vIn[4], mRow2);
R0[5] = __vmsum4fp(vIn[5], mRow0);
R1[5] = __vmsum4fp(vIn[5], mRow1);
R2[5] = __vmsum4fp(vIn[5], mRow2);
R0[6] = __vmsum4fp(vIn[6], mRow0);
R1[6] = __vmsum4fp(vIn[6], mRow1);
R2[6] = __vmsum4fp(vIn[6], mRow2);
R0[7] = __vmsum4fp(vIn[7], mRow0);
R1[7] = __vmsum4fp(vIn[7], mRow1);
R2[7] = __vmsum4fp(vIn[7], mRow2);
__stvewx(R0[0], OutputVector, 0);
__stvewx(R1[0], OutputVector, 4);
__stvewx(R2[0], OutputVector, 8);
OutputVector++;
__stvewx(R0[1], OutputVector, 0);
__stvewx(R1[1], OutputVector, 4);
__stvewx(R2[1], OutputVector, 8);
OutputVector++;
__stvewx(R0[2], OutputVector, 0);
__stvewx(R1[2], OutputVector, 4);
__stvewx(R2[2], OutputVector, 8);
OutputVector++;
__stvewx(R0[3], OutputVector, 0);
__stvewx(R1[3], OutputVector, 4);
__stvewx(R2[3], OutputVector, 8);
OutputVector++;
__stvewx(R0[4], OutputVector, 0);
__stvewx(R1[4], OutputVector, 4);
__stvewx(R2[4], OutputVector, 8);
OutputVector++;
__stvewx(R0[5], OutputVector, 0);
__stvewx(R1[5], OutputVector, 4);
__stvewx(R2[5], OutputVector, 8);
OutputVector++;
__stvewx(R0[6], OutputVector, 0);
__stvewx(R1[6], OutputVector, 4);
__stvewx(R2[6], OutputVector, 8);
OutputVector++;
__stvewx(R0[7], OutputVector, 0);
__stvewx(R1[7], OutputVector, 4);
__stvewx(R2[7], OutputVector, 8);
OutputVector++;
}
}
while (vCurrent < vStreamEnd)
{
vIn[0] = __lvx(vCurrent->Base(), 0);
R0[0] = __vmsum4fp(vIn[0], mRow0);
R1[0] = __vmsum4fp(vIn[0], mRow1);
R2[0] = __vmsum4fp(vIn[0], mRow2);
__stvewx(R0[0], vCurrent->Base(), 0);
__stvewx(R1[0], vCurrent->Base(), 4);
__stvewx(R2[0], vCurrent->Base(), 8);
vCurrent++;
}
}
#endif // #if !defined(__SPU__)
#endif