* ggml : switch to F32 src1 in the CPU backend

Change the default computation for GGML_TYPE_F16 to use F32 for src1
data in matrix multiplications: vec_dot_type(F16) is now F32 and the dot
product goes through the new ggml_vec_dot_f16_f32 (x = F16 src0, y = F32
src1), so src1 is no longer quantized to F16 and worst-case inputs that
only fit in the F32 FP range are handled correctly.

- conv_2d/conv_3d: store im2col patches (the inner mul_mat src1) as F32
  and pass separate src0/src1 types to the inner mul_mat; the previous
  F16 patches made the inner mul_mat widen src1 into the conv work
  buffer, corrupting the patches and crashing on large inputs
- conv_transpose_1d/2d (F16 kernel): keep src1 in F32 in the work buffer
  and use ggml_vec_dot_f16_f32; update work buffer planning accordingly
- supports_op: restore MUL_MAT support for F16 src1, which is now
  widened to F32
- ggml_vec_dot_f16_f32: add GGML_SIMD support by converting chunks of x
  to F32 and reusing the F32 SIMD dot
- mul_mat/mul_mat_id: add TODOs for a more efficient F16 x F16 path that
  can be used if ggml_prec_get_src(dst, 1) allows converting src1 to F16

MUL_MAT f16 x f32 perf on M5 Ultra (GFLOPS):
- m=2048, n=512, k=16 : 120.9 -> 101.7
- m=2048, n=512, k=64 : 150.5 -> 344.2
- m=4096, k=14336 GEMV:    63 -> 343-415
- m=4096, n=512, k=14336: 65.6 -> 770.2

Assisted-by: dsh:llama.cpp/ggml-org/GLM-5.3-Flash-GGUF (Mac Studio, M5 Ultra, 256GB)

* cont : add some F16 x F32 vectorized paths

* cont : enable the fused F16 x F32 dot on AVX without FMA

The 256-bit fused path of ggml_vec_dot_f16_f32 required AVX2 and FMA,
so CPUs with AVX and F16C only fell back to the chunked conversion and
F16 decode was 4x slower than before. Enable it on __AVX__ && __F16C__
and accumulate with GGML_F32x8_FMA, which does mul + add without FMA.

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Co-authored-by: Pascal <admin@serveurperso.com>