[ROCm][PerfOptimizataion] Enable layernorm using ck_tile APIs #1806
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… of 1.f/x (ROCm#1688) Replace (more) exact calculation with hardware approximation. Benefits: Reduced code size. Improved performance for certain scenarios. Experiments show low reduction in precision. Experiments show no significant performance regressions. bfloat16 as well as float16 related calculations may benefit largely from this change. vectorized_layer_norm_kernel: Gains performance esp. for the following tensor shapes. Lower values for dim1 do not change performance significantly. dim1 = 8k-65k may gain considerable performance, but decline gradually with size. ``` dim0 dim1 ---- ---- 1024 8192 1024 16384 1024 32768 1024 65536 1024 131072 1024 262144 1024 524288 ``` Co-authored-by: Hashem Hashemi <[email protected]>
lcskrishna
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jerrymannil,
amathews-amd and
coderfeli
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Jenkins build for 1c8edefea13fda2915cd4bde42fac3d0fd961513 commit finished as FAILURE |
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Jenkins build for 4c2dcdc2fa414f2d223fcd7f27cc72fe5352a6e6 commit finished as FAILURE |
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This PR does the following: