The implementation of complex scalar * vector multiplication for Z14
makes some LAPACK tests fail because the numerical differences to the
reference implementation exceed the threshold (as can be seen by running
make lapack-test and replacing kernel/zarch/cscal.c with a generic
implementation for comparison).
The complex multiplication uses terms of the form a * b + c * d for both
real and imaginary parts. The assembly code (and compiler-emitted code
as well) uses fused multiply add operations for the second product and
sum. The results can be "surprising", for example when both terms in the
imaginary part nearly cancel each other out. In that case, the second
product contributes more digits to the sum than the first product that
has been rounded before.
One option is to use separate multiplications (which then round the same
way) and a distinct add. Change the code to pursue that path, by (1)
requesting the compiler not to contract the operations into FMAs and (2)
replacing the assembly kernel with corresponding vectorized C code
(where change 1 also applies).
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
The code for SGEMM 16x4 and DGEMM 8x4 blocks on z14 and z15 uses
explicit unrolling and interleaving to improve performance. The code
employs an empty inline asm statement with operands that constrain the
compiler's instruction scheduling and thereby enforce proper overlapping
of load and compute phases. Fix an ifdef to apply that for clang builds,
as well.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
... since it is not required and clang does not support that gcc
extension. Instead, use a variable-length array directly for these
operands.
Note that, while the actual inline assembly code does not directly use
these memory operands, they serve to inform the compiler that it cannot
reorder reads or writes to/from the input and output data across the
inline asm statements.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
... since clang does not support the instruction format for inline
assembly and also it is not required for current versions of clang.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
... as a bandaid for building with clang until LLVM's internal assembler
supports nops without operand.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Some of the kernels written in assembly utilize a "load address"
instruction for loading an immediate value into a register. That is
both unnecessarily complex and LLVM's assembler does not understand that
specific syntax. Thus, replace with the appropriate "load immediate"
instruction, which is also clearer to read.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
For small register blockings that are too small to fill up vector
registers with column vectors, we currently use a generic code block.
Replace that with instantiations of the generic code as individual
functions, so that the compiler can optimize each one separately.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Improve performance of SGEMM and DGEMM on z14 and z15 by unrolling and
interleaving the inner loop of the SGEMM 16x4 and DGEMM 8x4 blocks.
Specifically, we explicitly interleave vector register loads and
computation of two iterations.
Note that this change only adds one C function, since SGEMM 16x4 and
DGEMM 8x4 actually map to the same C code: they both hold intermediate
results in a 4x4 grid of vector registers, and the C implementation is
built around that.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Apply our new GEMM kernel implementation, written in C with vector intrinsics,
also for DGEMM and DTRMM on Z14 and newer (i.e., architectures with FP32 SIMD
instructions). As a result, we gain around 10% in performance on z15, in
addition to improving maintainability.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
... since it gains another ~2% of SGEMM and DGEMM performance on z15;
also, the code just called for that cleanup.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Introduce inline assembly so that we can employ vector loads with
alignment hints on older compilers (pre gcc-9), since these are still
used in distributions such as RHEL 8 and Ubuntu 18.04 LTS.
Informing the hardware about alignment can speed up vector loads. For
that purpose, we can encode hints about 8-byte or 16-byte alignment of
the memory operand into the opcodes. gcc-9 and newer automatically emit
such hints, where applicable. Add a bit of inline assembly that achieves
the same for older compilers. Since an older binutils may not know about
the additional operand for the hints, we explicitly encode the opcode in
hex.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Change register blocking for SGEMM (and STRMM) on z14 from 8x4 to 16x4
by adjusting SGEMM_DEFAULT_UNROLL_M and choosing the appropriate copy
implementations. Actually make KERNEL.Z14 more flexible, so that the
change in param.h suffices. As a result, performance for SGEMM improves
by around 30% on z15.
On z14, FP SIMD instructions can operate on float-sized scalars in
vector registers, while z13 could do that for double-sized scalars only.
Thus, we can double the amount of elements of C that are held in
registers in an SGEMM kernel.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Employ the newly added GEMM kernel also for STRMM on Z14. The
implementation in C with vector intrinsics exploits FP32 SIMD operations
and thereby gains performance over the existing assembly code. Extend
the implementation for handling triangular matrix multiplication,
accordingly. As added benefit, the more flexible C code enables us to
adjust register blocking in the subsequent commit.
Tested via make -C test / ctest / utest and by a couple of additional
unit tests that exercise blocking.
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
Add a new GEMM kernel implementation to exploit the FP32 SIMD
operations introduced with z14 and employ it for SGEMM on z14 and newer
architectures.
The SIMD extensions introduced with z13 support operations on
double-sized scalars in vector registers. Thus, the existing SGEMM code
would extend floats to doubles before operating on them. z14 extended
SIMD support to operations on 32-bit floats. By employing these
instructions, we can operate on twice the number of scalars per
instruction (four floats in each vector registers) and avoid the
conversion operations.
The code is written in C with explicit vectorization. In experiments,
this kernel improves performance on z14 and z15 by around 2x over the
current implementation in assembly. The flexibilty of the C code paves
the way for adjustments in subsequent commits.
Tested via make -C test / ctest / utest and by a couple of additional
unit tests that exercise blocking (e.g., partial register blocks with
fewer than UNROLL_M rows and/or fewer than UNROLL_N columns).
Signed-off-by: Marius Hillenbrand <mhillen@linux.ibm.com>
The ZARCH implementations of ?sum contain a cut & paste-error: An inline
assembly argument is named "sum", but the assembly references "asum"
instead. The mismatch causes a build error. This is fixed.
Martin Kroeker
Marius Hillenbrand
int_13h
Andreas Arnez
maamountki