1. Added bfloat16 based dot as new API: shdot
2. Implemented generic kernel and cooperlake-specific (AVX512-BF16) kernel for shdot
3. Added 4 conversion APIs for bfloat16 data type <=> single/double: shstobf16 shdtobf16 sbf16tos dbf16tod
     shstobf16 -- convert single float array to bfloat16 array
     shdtobf16 -- convert double float array to bfloat16 array
     sbf16tos  -- convert bfloat16 array to single float array
     dbf16tod  -- convert bfloat16 array to double float array
4. Implemented generic kernels for all 4 conversion APIs, and cooperlake-specific kernel for shstobf16 and shdtobf16
5. Update level1 thread facilitate functions and macros to support multi-threading for these new APIs
6. Fix Cooperlake platform detection/specify issue when under dynamic-arch building
7. Change the typedef of bfloat16 from unsigned short to more strict uint16_t

Signed-off-by: Chen, Guobing <guobing.chen@intel.com>

Move "direct SGEMM" functionality out of the SkylakeX SGEMM kernel and make it available
(on x86_64 targets only for now) in DYNAMIC_ARCH builds
* Add  sgemm_direct targets in the kernel Makefile.L3 and CMakeLists.txt
* Add direct_sgemm functions to the gotoblas struct in common_param.h
* Move sgemm_direct_performant helper to separate file
* Update gemm.c  to macros for sgemm_direct to support dynamic_arch naming via common_s,h
* (Conditionally) add sgemm_direct functions in setparam-ref.c

* make building the bfloat16 BLAS functions conditional on BUILD_HALF

* pass the BUILD_HALF option to gensymbol

* Pass BUILD_HALF as a compiler define for dynamic_arch builds

This patch adds support for bfloat16 data type matrix multiplication kernel.
For architectures that don't support bfloat16, it is defined as unsigned short
(2 bytes).  Default unroll sizes can be changed as per architecture as done for
SGEMM and for now 8 and 4 are used for M and N.  Size of ncopy/tcopy can be
changed as per architecture requirement and for now, size 2 is used.

Added shgemm in kernel/power/KERNEL.POWER9 and tested in powerpc64le and
powerpc64.  For reference, added a small test compare_sgemm_shgemm.c to compare
sgemm and shgemm output.

This patch does not cover OpenBLAS test, benchmark and lapack tests for shgemm.
Complex type implementation can be discussed and added once this is approved.

fix error messages

Found via `codespell -q 3 -w -L ith,als,dum,nd,amin,nto,wis,ba -S ./relapack,./kernel,./lapack-netlib`

Correct length of name string in xerbla call

Provide CBLAS interfaces to I?MIN and I?MAX

revert workaround introduced for issue #1332 as the actual cause appears to be my incorrect fix from #1262 (see #1388)

See #1886 and JuliaRobotics issue 500. trsm benchmarks on Haswell and Zen showed that with these values performance is roughly doubled for matrix sizes between 8x8 and 14x14, and still 10 to 20 percent better near the new cutoff at 32x32.

OpenBLAS has a fancy algorithm for copying the input data while laying
it out in a more CPU friendly memory layout.

This is great for large matrixes; the cost of the copy is easily
ammortized by the gains from the better memory layout.

But for small matrixes (on CPUs that can do efficient unaligned loads) this
copy can be a net loss.

This patch adds (for SKYLAKEX initially) a "sgemm direct" mode, that bypasses
the whole copy machinary for ALPHA=1/BETA=0/... standard arguments,
for small matrixes only.

What is small? For the non-threaded case this has been measured to be
in the M*N*K = 28 * 512 * 512 range, while in the threaded case it's
less, around M*N*K = 1 * 512 * 512

Handle special case INCX=0,INCY=0 in the axpy interface

disable threading in C/ZSWAP copying from S/DSWAP

Delay _hemv threading in attempt to address #1820

Currently the generic ARMV8 target uses C implementations
for many routines. Replace these with the neon implementations
written for THUNDERX2T99 target which are upto 6x faster for
certain routines.

Add explicit casts to silence compiler warnings

for #1710

for #1710

Introduce blasabs macro and use it to switch between abs and labs for INTERFACE64

Fixes two calls that were using `fabs` on a `long double` argument rather than `fabsl`, which looks like it is doing an unintentional truncation to `double` precision.

I don't have as many benchmarks for these as for gemm, but it should still
make a difference for small matrices.

Always checking num_cpu_avail() regardless of whether threading will actually
be used adds noticeable overhead for small matrices.  Most other uses of
num_cpu_avail() do so only if threading will be used, so do the same here.

copies daxpy improvement from #27, see #1560

Disable multithreading in ztrmv

BLAS-Tester shows that the same problem exists as with DTRMV (issue #1332)

* Rewrite ROTMG based on the new implementation in GONUM based on the algorithm proposed by Tim Hopkins, see issue 1452 for the reference
* Correct ROTMG utest for issue1452 and add another from gonum, also correct transposition of expected and observed values in error messages