Out of Order: Making In-Order Processors Play Nicely (presented by Allan Murphy)

VMX on the 360 for optimization of vector math

Slower than C counterpart, and out of order (so broken)

Missing out of order logic

• no instruction reordering
• no store forward hardware
• smaller caches, slower memory
• no l3 cache

 

• LHS
• L2 Miss
• Expensive, non pipelined instructions
• Branch mispredict penalty

Load Hit Store

• Store to memory location, then load, flush the L2 cache
• Casts, changing register set, aliasing
• Passing by value, or by reference
• On Pc, instruction reoder and store / forward hardware

L2 Miss

• Loading from location, checks cache
• Cost ~610 cycles to load cache line
• Hot cold split
• Reduce in-memory data size
• Use cache coherent structures

Expensive Instructions

• non pipelined instructions
• Stalls hardware threads

Branch Mispredict

• Mispredicting branch
• 23-24 cycle delay
• Know how the compiler implements branches
• Reduce total branch count for task
• Refactor calculations to remove branches
• Unroll

Profiling!!!

360 Tools

• PIX Cpu instruction trace
• LibPMCPB counters
• XbPerfView sampling capture

Other Platforms

• SN Tuner, vTune

Think laterally

• Inline functions
• pass and return in register (_declspec(passinreg)
• _restrict (complier released from being ultra careful
• const

 

Compiler options

• Inline
• Prefer speed over size
• Fast floaging point over precise
• 360 (/Ou removing div by zero, /Oc runs a second code scheduling pass)
• Reduce parameter counts
• Prefer 32, 64, 128 bit parameters
• Isoloate constants
• Avoid virtual if feasible

Know you cache architecture

• Cross core sharing policy (L2 shared, L1 single)
• Prefetch mech (dcbt, dcbz128)
• L2 1MB, L1 32Kb
• Cache line 128 byte

Know your instruction set

• 360 specific (VMX, slow instructions, fsel, vsel, vcmp*, vrlimi)
• PS3 (altivec)
• PC (SSE2-4.1 and friends)

What went wrong

• Correctness
• Guessed at 1 perf issue
• SIMD vs straight float
• Memory access and L2 usage unchanged
• Branch behavior exactly the same

Image Analysis

• Gaussian Mixture Model
• Profiling showed (86% tiem in pixel cost function)