Fix device issue with CL softmax
* Performing the second pass in reverse order doesn't seem to work
reliably in some specific devices. This patch introduces
another approach to workaround the device issue.
Resolves: COMPMID-6669
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I591f05ff06f8439ebe4d32093441ae871a292f4c
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10730
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/common/softmax_layer.cl b/src/core/CL/cl_kernels/common/softmax_layer.cl
index 58c4589..bfc0995 100644
--- a/src/core/CL/cl_kernels/common/softmax_layer.cl
+++ b/src/core/CL/cl_kernels/common/softmax_layer.cl
@@ -272,6 +272,22 @@
dst_ptr += dst_offset_first_element + dim_2 * dst_stride_2 + dim_1 * dst_stride_1 + dim_0 * dst_stride_0;
tmp_ptr += tmp_offset_first_element + dim_2 * tmp_stride_2 + dim_1 * tmp_stride_1 + dim_0 * tmp_stride_0;
+ // In case of processing quantized data, i.e. DATA_TYPE is smaller than TMP_DATA_TYPE:
+ //
+ // In the first pass (finding max), the quantized data is copied from the input tensor to the temporary tensor.
+ // Dequantization is not needed to find the max value and since dequantization widens the data, we defer it
+ // to the second pass pass to reduce memory bandwidth of the first pass.
+ //
+ // In the second pass, it reads the quantized data from the temporary tensor and writes the dequantized data
+ // back to the temporary tensor.
+ //
+ // To avoid dequantized data overwritting the unprocessed quantized data in the temporary tensor,
+ // this extra offset is introduced to store the quantized data at the end of the temporary tensor.
+ //
+ // Note: Another approach is to perform the second pass in reverse order, but for unexplanable reason
+ // it doesn't work in some devices.
+ uint tmp_extra_offset = LENGTH * VEC_SIZE * (sizeof(TMP_DATA_TYPE) - sizeof(DATA_TYPE));
+
// Calculate max value and store the input data to the temporary tensor in suitable format.
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) max_value = MIN_VALUE;
int i = 0;
@@ -282,7 +298,7 @@
max_value = max(max_value, data);
- VSTORE(VEC_SIZE)(data, 0, (__global DATA_TYPE *)(tmp_ptr + i * VEC_SIZE * sizeof(DATA_TYPE)));
+ VSTORE(VEC_SIZE)(data, 0, (__global DATA_TYPE *)(tmp_ptr + tmp_extra_offset + i * VEC_SIZE * sizeof(DATA_TYPE)));
}
// Regularize the data.
@@ -296,18 +312,9 @@
# define REGULARIZE(x) (((x) - max_value) * (TMP_DATA_TYPE)BETA)
#endif // IS_QUANTIZED
- for (i = LENGTH - 1; i >= 0; --i)
+ for (i = 0; i < LENGTH; ++i)
{
- // In case of processing quantized data, i.e. DATA_TYPE is smaller than TMP_DATA_TYPE:
- //
- // In the first pass (finding max), the quantized data is copied from the input tensor to the temporary tensor.
- // Dequantization is not needed to find the max value and since dequantization widens the data, we defer it
- // to the second pass pass to reduce memory bandwidth of the first pass.
- //
- // This pass reads the quantized data from the temporary tensor and writes the dequantized data
- // back to the temporary tensor, hence we need to loop in reverse to avoid overwriting unprocessed data.
-
- VEC_DATA_TYPE(TMP_DATA_TYPE, VEC_SIZE) data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(tmp_ptr + i * VEC_SIZE * sizeof(DATA_TYPE))), VEC_DATA_TYPE(TMP_DATA_TYPE, VEC_SIZE));
+ VEC_DATA_TYPE(TMP_DATA_TYPE, VEC_SIZE) data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(tmp_ptr + tmp_extra_offset + i * VEC_SIZE * sizeof(DATA_TYPE))), VEC_DATA_TYPE(TMP_DATA_TYPE, VEC_SIZE));
data = REGULARIZE(data);