On Fri, 26 Sep 2025 12:00:31 GMT, Bhavana Kilambi <[email protected]> wrote:

> This patch adds mid-end support for vectorized add/mul reduction operations 
> for half floats. It also includes backend aarch64 support for these 
> operations. Only vectorization support through autovectorization is added as 
> VectorAPI currently does not support Float16 vector species.
> 
> Both add and mul reduction vectorized through autovectorization mandate the 
> implementation to be strictly ordered. The following is how each of these 
> reductions is implemented for different aarch64 targets -
> 
> **For AddReduction :**
> On Neon only targets (UseSVE = 0): Generates scalarized additions using the 
> scalar `fadd` instruction for both 8B and 16B vector lengths. This is because 
> Neon does not provide a direct instruction for computing strictly ordered 
> floating point add reduction.
> 
> On SVE targets (UseSVE > 0): Generates the `fadda` instruction which computes 
> add reduction for floating point in strict order.
> 
> **For MulReduction :**
> Both Neon and SVE do not provide a direct instruction for computing strictly 
> ordered floating point multiply reduction. For vector lengths of 8B and 16B, 
> a scalarized sequence of scalar `fmul` instructions is generated and multiply 
> reduction for vector lengths > 16B is not supported.
> 
> Below is the performance of the two newly added microbenchmarks in 
> `Float16OperationsBenchmark.java` tested on three different aarch64 machines 
> and with varying `MaxVectorSize` -
> 
> Note: On all machines, the score (ops/ms) is compared with the master branch 
> without this patch which generates a sequence of loads (`ldrsh`) to load the 
> FP16 value into an FPR and a scalar `fadd/fmul` to add/multiply the loaded 
> value to the running sum/product. The ratios given below are the ratios 
> between the throughput with this patch and the throughput without this patch.
> Ratio > 1 indicates the performance with this patch is better than the master 
> branch.
> 
> **N1 (UseSVE = 0, max vector length = 16B):**
> 
> Benchmark         vectorDim  Mode   Cnt  8B     16B
> ReductionAddFP16  256        thrpt  9    1.41   1.40
> ReductionAddFP16  512        thrpt  9    1.41   1.41
> ReductionAddFP16  1024       thrpt  9    1.43   1.40
> ReductionAddFP16  2048       thrpt  9    1.43   1.40
> ReductionMulFP16  256        thrpt  9    1.22   1.22
> ReductionMulFP16  512        thrpt  9    1.21   1.23
> ReductionMulFP16  1024       thrpt  9    1.21   1.22
> ReductionMulFP16  2048       thrpt  9    1.20   1.22
> 
> 
> On N1, the scalarized sequence of `fadd/fmul` are generated for both 
> `MaxVectorSize` of 8B and 16B for add reduction ...

I seem to have a failure on 
`compiler/vectorization/TestFloat16VectorOperations.java` on aarch64
in `C2_MacroAssembler::neon_reduce_add_fp16(FloatRegister, FloatRegister, 
FloatRegister, unsigned int, FloatRegister)` at 
`src/hotspot/cpu/aarch64/c2_MacroAssembler_aarch64.cpp:1930`:

assert(vector_length_in_bytes == 8 || vector_length_in_bytes == 16) failed: 
unsupported

-------------

PR Comment: https://git.openjdk.org/jdk/pull/27526#issuecomment-3339456935

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