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Vector Units and Quaternions

Vector Units and Quaternions. Jim Van Verth Red Storm Entertainment jimvv@redstorm.com. About This Talk. Will discuss how to do quaternion math on PS2 Assume that you already know and want to use quaternions Assume that you already know something about how the VU works. About Me.

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Vector Units and Quaternions

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  1. Vector Units and Quaternions Jim Van Verth Red Storm Entertainment jimvv@redstorm.com

  2. About This Talk • Will discuss how to do quaternion math on PS2 • Assume that you already know and want to use quaternions • Assume that you already know something about how the VU works

  3. About Me • Lead engineer at Red Storm Entertainment • Not a quaternion god • Not a vector unit god • Not really familiar with VCL • Just a 3D guy trying to get by…

  4. About the code • Most examples written in macro mode (VU0) • Easy to translate to micro mode • Examples that would be faster in micro mode are discussed separately

  5. Matrices on PS2 • PS2 is really well set up to do matrices • Multiplies are highly parallel • Not so good for quaternions

  6. This is what we’re up against Takes 4/7 cycles to transform a point Takes 16/19 cycles to concat matrices (9/12 cycles for 3x3 matrix) Matrix Multiply vmulax ACC, vf2, vf1x vmadday ACC, vf3, vf1y vmaddaz ACC, vf4, vf1z vmaddw vf6, vf5, vf1w

  7. Why Quaternions? • Quaternions take up less space: 4 floats vs. 9 (best case) • Quaternions interpolate well • Avoid floating point drift (normalize vs. Gram-Schmidt orthogonalization)

  8. Quaternions on VU • Fit very well • Four floats, aligned to 16-bit boundary • Work just like homogeneous point • Make sure stored (x,y,z,w) not (w,x,y,z)

  9. Quaternion Multiplication • If quaternion is (x, y, z,w) or (v, w) then • All standard vector operations • Add, scale, dot product, cross product

  10. Interleaves dot product and rest via accumulator Takes advantage of linearity of cross product Cycle count: 8/11 Less than matrix! Quaternion Mult on PS2 vmul vf3, vf1, vf2 vopmula.xyz acc, vf1, vf2 vmaddaw.xyz acc, vf2, vf1w vmaddaw.xyz acc, vf1, vf2w vopmsub.xyz vf3, vf2, vf1vsubaz.w acc, vf3, vf3z vmsubax.w acc, vf0, vf3x vmsuby.w vf3, vf0, vf3y w= w1·w2v1 • v2 v = w1·v2 + w2·v1 + v1v2

  11. Vector Rotation • Formula for vector rotation: • Two mults takes 16 cycles, plus the inverse • Can do better

  12. Vector Rotation, Take Two • If q is normalized, then can do: • This is faster than two straight multiplies on serial processor • Faster on vector processor, too!

  13. pin vf1, q in vf2 Vector Rotation on VU vmul vf11, vf1, vf2 vopmula.xyz acc, vf2, vf1 vopmsub.xyz vf5, vf1, vf2 vmul.w vf6w, vf2w, vf2w vadd.w vf7w, vf2w, vf2wvmulax.w accw, vf0w, vf11x vmadday.w accw, vf0w, vf11y vmaddz.w vf11w, vf0w, vf11z vopmula.xyz acc, vf2, vf5 vmaddaw.xyz acc, vf5, vf7w vmaddaw.xyz acc, vf1, vf6w vmaddaw.xyz acc, vf2, vf11w vopmsub.xyz vf3, vf5, vf2 p =(vp)·v + w2·p + 2w·(vp) + v(vp)

  14. First part builds all the pieces Second part adds ‘em all together Cycles: 13/16 Better than straight multiply Worse than matrix Vector Rotation on VU vmul vf11, vf1, vf2 vopmula.xyz acc, vf2, vf1 vopmsub.xyz vf5, vf1, vf2 vmul.w vf6w, vf2w, vf2w vadd.w vf7w, vf2w, vf2wvmulax.w accw, vf0w, vf11x vmadday.w accw, vf0w, vf11y vmaddz.w vf11w, vf0w, vf11z vopmula.xyz acc, vf2, vf5 vmaddaw.xyz acc, vf5, vf7w vmaddaw.xyz acc, vf1, vf6w vmaddaw.xyz acc, vf2, vf11w vopmsub.xyz vf3, vf5, vf2

  15. Full Transforms • Combination of translation vector t, quat r, 3 scale factors s • Once again, want to transform point • Basic formula:

  16. pin vf1, q in vf2 scale in vf3 translation in vf4 Takes four extra cycles for scale (including stalls), one extra for xlate Cycle count: 18/21 Point Transformation vmul vf1, vf1, vf3 vmul vf11, vf1, vf2 vopmula.xyz acc, vf2, vf1 vopmsub.xyz vf5, vf1, vf2 vmul.w vf6w, vf2w, vf2w vadd.w vf7w, vf2w, vf2w vmulax.w accw, vf0w, vf11x vmadday.w accw, vf0w, vf11y vmaddz.w vf11w, vf0w, vf11z vopmula.xyz acc, vf2, vf5 vmaddaw.xyz acc, vf5, vf7w vmaddaw.xyz acc, vf1, vf6w vmaddaw.xyz acc, vf2, vf11w vmaddaw.xyz acc, vf4, vf0w vopmsub.xyz vf3, vf5, vf2

  17. Transform Concatenation • Look at formula: • Have to transform point and multiply two quaternions and multiply scales

  18. Transform Concatenation • Takes 8 cycles for quat multiply, 18 for transform, 1 for scale • Have three stall cycles available • Bottom line: 24/27 cycles • Much slower than matrix multiplication • Not recommended

  19. Matrix Conversion • Quat-vector transformation not as efficient as matrix-vector transformation (13 cycles vs. 4) • To do multiple points, want to convert quaternion to a 4x4 matrix

  20. Matrix Conversion • Corresponding 4x4 matrix to normalized quat q = (x,y,z,w) is: • Not obvious how to do this efficiently

  21. Matrix Conversion • Two approaches • One works well in macro mode • One in micro mode • uses Lower instructions to achieve better parallelism

  22. Matrix Conversion (macro) • Idea: matrix is built from two other matrices

  23. Matrix Conversion (macro) • Simplification: matrix multiply is series of row vector multiplies • Create right matrix, generate left matrix via accumulator tricks

  24. Matrix Conversion (macro) • Look at one row in matrix multiply: vmulax ACC, vf5, vf1x vmadday ACC, vf6, vf1y vmaddaz ACC, vf7, vf1z vmaddw vf9, vf8, vf1w • Or could just do: vmulaw ACC, vf8, vf1w vmadday ACC, vf6, vf1y vmaddaz ACC, vf7, vf1z vmaddx vf9, vf5, vf1x • Is linear, so order doesn’t matter

  25. Matrix Conversion (macro) • Idea: all values we need for left matrix are in quaternion • Load accumulator with mula by w value (always positive) • vmadd or vmsub to multiply by positive or negative value and accumulate vmulaw.xyz acc, vf2, vf5w vmaddax.xyz acc, vf3, vf5x vmadday.xyz acc, vf4, vf5y vmsubz.xyz vf13, vf1, vf5z

  26. Matrix Conversion (macro) • More simplification: • Last row of Mq always (0,0,0,1), don’t compute! • Last column always 0 too, don’t compute! • Last row of Rq just the quat in VU format • Just build:

  27. vaddw.x vf1, vf0, vf4 vaddz.y vf1, vf0, vf4 vsuby.z vf1, vf0, vf4 vsubz.x vf2, vf0, vf4 vaddw.y vf2, vf0, vf4 vaddx.z vf2, vf0, vf4 vaddy.x vf3, vf0, vf4 vsubx.y vf3, vf0, vf4 vaddw.z vf3, vf0, vf4 vmr32.w vf12, vf0 vmr32.w vf13, vf0 vmr32.w vf14, vf0 Stage one: Load quat in vf4 Build right matrix Clear right column of result vf1=(w,z,-y,~) vf2=(-z,w,x,~) vf3=(y,-x,w,~) vf4=(x,y,z,w) Matrix Conversion (macro)

  28. vmulaw.xyz acc, vf1, vf4w vmaddaz.xyz acc, vf2, vf4z vmsubay.xyz acc, vf3, vf4y vmaddx.xyz vf12, vf4, vf4x vmulaw.xyz acc, vf2, vf4w vmaddax.xyz acc, vf3, vf4x vmadday.xyz acc, vf4, vf4y vmsubz.xyz vf13, vf1, vf4z vmulaw.xyz acc, vf3, vf4w vmaddaz.xyz acc, vf4, vf4z vmadday.xyz acc, vf1, vf4y vmsubx.xyz vf14, vf2, vf4x vmove.xyzw vf15, vf0 Stage two: Matrix multiply to get first three rows Clear bottom row Note: accumulate only on xyz (w already cleared) Cycles: 25/28 Matrix Conversion (macro)

  29. Matrix Conversion (micro) • Lots of duplicate calculations in matrix • Idea: calculate only what we need, use shifting and accumulator tricks to parallelize efficiently • Devised by Colin Hughes of SCEE

  30. mula acc, vf1, vf1 loi SQRT_2 muli vf3, vf1, Imr32.w vf24, vf0 madd vf2, vf1, vf1 nop addw vf4, vf0, vf0w nop opmula acc, vf3, vf3move vf27, vf0 msubw vf5, vf3, vf3wmr32.w vf26, vf0 maddw vf6, vf3, vf3wmr32.w vf25, vf0 addaw.xyz acc, vf0, vf0w nop msubax.yz acc, vf4, vf2x nop msuby.z vf26, vf4, vf2ymr32 vf3, vf5 msubay.xz acc, vf4, vf2ymr32 vf7, vf6 msubz.y vf25, vf4, vf2z mr32.y vf24, vf5 msubz.x vf24, vf4, vf2z mr32.x vf26, vf5 addy.z vf24, vf0, vf6y mr32.z vf25, vf3 addx.y vf26, vf0, vf6x mr32.x vf25, vf7 Three parts Calculate elements Clear matrix Shift, add and copy into place 16/19 cycles Matrix Conversion (micro)

  31. Matrix Conversion • If you’re converting a quaternion and going to use it immediately, can make some assumptions • Don’t create bottom row (just use vf0) • Don’t clear right column (just use xyz) • Saves four cycles in macro mode case

  32. Transform to Matrix • Use one of the quaternion matrix techniques • Scale first three rows by each scale factor • Replace last row with translation • Results: • 29/32 for macro mode • 20/23 for micro mode

  33. Normalization • Need to normalize quaternion to keep it useful for rotation • (Also avoids floating point drift) • Fortunately PS2 has reciprocal square root instruction • Unfortunately it takes a while

  34. vmul vf2, vf1, vf1 vaddaz.w acc, vf2, vf2 vmaddax.w acc, vf0, vf2 vmaddy.w vf2, vf0, vf2 vrsqrt Q, vf0w, vf2w vwaitq vmulq vf1, vf1, Q Compute dot product Compute 1/length Scale quaternion With stalls, takes 24/27 cycles Normalization

  35. Normalization • Another approach • From “The Inner Product”, March 2002 Game Developer by Jonathan Blow • Approximate 1/x via Newton-Raphson iteration • First iteration takes (looks like) 4/7 cycles on VU0 • Second iteration takes as long as RSQRT • Recommend: if x > 0.91521198, use approx • Otherwise use RSQRT

  36. Interpolation • This is where it’s at • It would be great if it was fast • Um, well…

  37. Interpolation • First look at spherical linear interp • That’s a lot of sines • Could precompute , 1/sin  • But at least 28 cycles for one of the other sines • We (RSE) don’t use slerp anyway

  38. Interpolation • Lerp, then • is simply(q in vf1, r in vf2, t in vf3w) • vaddax acc, vf1, vf0x • vmsubaw acc, vf1, vf3w • vmaddw vf1, vf2,vf3w • Need to normalize afterwards • Makes 30/33 cycles

  39. Interpolation • Not quite that simple • Problem: if q•r < 0, interpolation will take long way around sphere • Need to negate one quat • Gives the same orientation, but the interpolation takes the short route

  40. vmul vf4, vf1, vf2 vaddaz.w acc, vf04, vf4 vmaddax.w acc, vf00, vf4 vmaddy.w vf4, vf00, vf4 vnop vnop vnop cfc2 t0,$16 and t0,t0,0x0002 vaddax acc, vf1, vf0x beq t0,zero,Add vmsubaw acc, vf2,vf3w b Finish Add:vmaddaw acc, vf2,vf3w Finish:vmsubw vf1, vf1, vf3w Compute dot product Check for negative Interpolate Follow up with normalization Takes 43/46 cycles Linear Interpolation

  41. Linear Interpolation • There’s more we can do • Jonathan Blow’s article, again • Use spline to correct error in lerp • More investigation needed • Initial results: takes about 24-26 more cycles • Looks faster than slerp, more accurate than lerp

  42. How We’re Using All This • A bit research-y at the moment • VU0-based math library • Optimization in specific routines • In particular, concatenation and interpolation for bones animation • More memory savings: store quat as 4.12 fixed-point shorts

  43. Conclusions • Quaternions useful on PS2 • Cheaper to concatenate (alone) • Convert to matrix to transform • Use linear interpolation • Check out Jonathan Blow’s article

  44. References • Shoemake, Ken, “Animating Rotation with Quaternion Curves,” Computer Graphics, Vol. 19, No. 3 (July 1985). • EE Core Instruction Set Manual • VU User’s Manual • Sony newsgroups • Blow, Jonathan, “Hacking Quaternions,” Game Developer, Vol. 9, No. 3 (March 2002). [get updated source from www.gdmag.com/code.htm]

  45. Questions?

  46. Please hand in comment sheets • Slides available at: http://obiwan.redstorm.com/~jimvv

  47. Vector Units and Quaternions Jim Van Verth Red Storm Entertainment jimvv@redstorm.com

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