[LLVMdev] IndVar widening in IndVarSimplify causing performance regression on GPU programs

Andrew Trick atrick at apple.com
Fri Oct 24 15:15:37 PDT 2014

Please see: http://llvm.org/PR21148 <http://llvm.org/PR21148>

I updated the bug with my suggestion. I hope it works.


> On Oct 24, 2014, at 11:29 AM, Justin Holewinski <jholewinski at nvidia.com> wrote:
> On Fri, 24 Oct 2014, Jingyue Wu wrote:
>> Hi, 
>> I noticed a significant performance regression (up to 40%) on some internal CUDA benchmarks (a reduced example presented below). The root cause of this regression seems
>> that IndVarSimpilfy widens induction variables assuming arithmetics on wider integer types are as cheap as those on narrower ones. However, this assumption is wrong at
>> least for the NVPTX64 target. 
>> Although the NVPTX64 target supports 64-bit arithmetics, since the actual NVIDIA GPU typically has only 32-bit integer registers, one 64-bit arithmetic typically ends up
>> with two machine instructions taking care of the low 32 bits and the high 32 bits respectively. I haven't looked at other GPU targets such as R600, but I suspect this
>> problem is not restricted to the NVPTX64 target. 
>> Below is a reduced example:
>> __attribute__((global)) void foo(int n, int *output) {
>>   for (int i = 0; i < n; i += 3) {
>>     output[i] = i * i;
>>   }
>> }
>> Without widening, the loop body in the PTX (a low-level assembly-like language generated by NVPTX64) is:
>> BB0_2:                                  // =>This Inner Loop Header: Depth=1        
>>         mul.lo.s32      %r5, %r6, %r6;                                              
>>         st.u32  [%rd4], %r5;                                                        
>>         add.s32         %r6, %r6, 3;                                                
>>         add.s64         %rd4, %rd4, 12;                                              
>>         setp.lt.s32     %p2, %r6, %r3;
>>         @%p2 bra        BB0_2;
>> in which %r6 is the induction variable i. 
>> With widening, the loop body becomes:
>> BB0_2:                                  // =>This Inner Loop Header: Depth=1        
>>         mul.lo.s64      %rd8, %rd10, %rd10;                                         
>>         st.u32  [%rd9], %rd8;                                                         
>>         add.s64         %rd10, %rd10, 3;                                            
>>         add.s64         %rd9, %rd9, 12;                                             
>>         setp.lt.s64     %p2, %rd10, %rd1;                                           
>>         @%p2 bra        BB0_2;
>> Although the number of PTX instructions in both versions are the same, the version with widening uses more mul.lo.s64, add.s64, and setp.lt.s64 instructions which are
>> more expensive than their 32-bit counterparts. Indeed, the SASS code (disassembly of the actual machine code running on GPUs) of the version with widening looks
>> significantly longer. 
>> Without widening (7 instructions): 
>> .L_1:                                                                               
>>         /*0048*/                IMUL R2, R0, R0;                                      
>>         /*0050*/                IADD R0, R0, 0x1;                                   
>>         /*0058*/                ST.E [R4], R2;                                      
>>         /*0060*/                ISETP.NE.AND P0, PT, R0, c[0x0][0x140], PT;             /*0068*/                IADD R4.CC, R4, 0x4;                                
>>         /*0070*/                IADD.X R5, R5, RZ;                                  
>>         /*0078*/            @P0 BRA `(.L_1);
>> With widening (12 instructions):
>> .L_1:                                                                            
>>         /*0050*/                IMUL.U32.U32 R6.CC, R4, R4;                      
>>         /*0058*/                IADD R0, R0, -0x1;                                    
>>         /*0060*/                IMAD.U32.U32.HI.X R8.CC, R4, R4, RZ;             
>>         /*0068*/                IMAD.U32.U32.X R8, R5, R4, R8;                   
>>         /*0070*/                IMAD.U32.U32 R7, R4, R5, R8;                     
>>         /*0078*/                IADD R4.CC, R4, 0x1;                             
>>         /*0088*/                ST.E [R2], R6;                                   
>>         /*0090*/                IADD.X R5, R5, RZ;                               
>>         /*0098*/                ISETP.NE.AND P0, PT, R0, RZ, PT;                 
>>         /*00a0*/                IADD R2.CC, R2, 0x4;                             
>>         /*00a8*/                IADD.X R3, R3, RZ;                                  
>>         /*00b0*/            @P0 BRA `(.L_1);
>> I hope the issue is clear up to this point. So what's a good solution to fix this issue? I am thinking of having IndVarSimplify consult TargetTransformInfo about the cost
>> of integer arithmetics of different types. If operations on wider integer types are more expensive, IndVarSimplify should disable the widening. 
> TargetTransformInfo seems like a good place to put a hook for this. You're right that 64-bit integer math will be slower for NVPTX targets, as the hardware needs to emulate 64-bit integer ops with 32-bit ops.
> How much is register usage affected by this in your benchmarks?
>> Another thing I am concerned about: are there other optimizations that make similar assumptions about integer widening? Those might cause performance regression too just
>> as IndVarSimplify does. 
>> Jingyue

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