Commit Graph

28 Commits

Author SHA1 Message Date
Vignesh Balasubramanian
327142395b Cleanup for readability and uniformity of Tiny-ZGEMM
- Guarded the inclusion of thresholds(configuration
  headers) using macros, to maintain uniformity in
  the design principles.

- Updated the threshold macro names for every
  micro-architecture.

AMD-Internal: [CPUPL-5895]
Change-Id: I9fd193371c41469d9ef38c37f9c055c21457b56c
2025-01-27 15:48:31 +05:30
Vignesh Balasubramanian
fb6dcc4edb Support for Tiny-GEMM interface(ZGEMM)
- As part of AOCL-BLAS, there exists a set of vectorized
  SUP kernels for GEMM, that are performant when invoked
  in a bare-metal fashion.

- Designed a macro-based interface for handling tiny
  sizes in GEMM, that would utilize there kernels. This
  is currently instantiated for 'Z' datatype(double-precision
  complex).

- Design breakdown :
  - Tiny path requires the usage of AVX2 and/or AVX512
    SUP kernels, based on the micro-architecture. The
    decision logic for invoking tiny-path is specific
    to the micro-architecture. These thresholds are defined
    in their respective configuration directories(header files).

  - List of AVX2/AVX512 SUP kernels(lookup table), and their
    lookup functions are defined in the base-architecture from
    which the support starts. Since we need to support backward
    compatibility when defining the lookup table/functions, they
    are present in the kernels folder(base-architecture).

- Defined a new type to be used to create the lookup table and its
  entries. This type holds the kernel pointer, blocking dimensions
  and the storage preference.

- This design would only require the appropriate thresholds and
  the associated lookup table to be defined for the other datatypes
  and micro-architecture support. Thus, is it extensible.

- NOTE : The SUP kernels that are listed for Tiny GEMM are m-var
         kernels. Thus, the blocking in framework is done accordingly.
         In case of adding the support for n-var, the variant
         information could be encoded in the object definition.

- Added test-cases to validate the interface for functionality(API
  level tests). Also added exception value tests, which have been
  disabled due to the SUP kernel optimizations.

AMD-Internal: [CPUPL-6040][CPUPL-6018][CPUPL-5319][CPUPL-3799]
Change-Id: I84f734f8e683c90efa63f2fa79d2c03484e07956
2025-01-24 12:59:26 -05:00
Vignesh Balasubramanian
cdaa2ac7fd Bugfix and optimizations for AVX512 AMAXV micro-kernels
- Bug : The current {S/D}AMAXV AVX512 kernels produced an
  incorrect functionality with multiple absolute maximums.
  They returned the last index when having multiple occurences,
  instead of the first one.

- Implemented a bug-fix to handle this issue on these AVX512
  kernels. Also ensured that the kernels are compliant with
  the standard when handling exception values.

- Further optimized the code by decoupling the logic to find
  the maximum element and its search space for index. This way,
  we use lesser latency instructions to compute the maximum
  first.

- Updated the unit-tests, exception value tests and early return
  tests for the API to ensure code-coverage.

AMD-Internal: [CPUPL-4745]
Change-Id: I2f44d33dbaf89fe19e255af1f934877816940c6f
2025-01-07 22:56:20 +05:30
Vignesh Balasubramanian
609af9bfe2 Threshold tuning for ZGEMM small path
- Updated the threshold check for ZGEMM small path to include
  runtime checks for redirection, specific to the micro-architecture.

- The current ZGEMM small path has only its AVX2 variant available.
  Post implementing an AVX512(same/different algorithm), the thresholds
  will further be fine-tuned.

- Included the dot-product based AVX512 ZGEMM kernels in the ZEN5
  context. It will be used as part of handling RRC and CRC storage
  schemes of C, A and B matrices in both single-thread and multi-thread
  runs.

AMD-Internal: [CPUPL-5949]
Change-Id: Ic8b7cf0e00b7c477f748669f160c4b01df995c75
2024-12-13 12:51:22 -05:00
Shubham Sharma.
be6fbadd95 BlockSize Tuning for ZEN4 and ZEN5
- Enabled dynamic blocksizes for DGEMM in ZEN4 and ZEN5 systems.
- MC, KC and NC are dynamically selected at runtime for DGEMM native.
- A local copy of cntx is created and blocksizes are updated in the local cntx.
- Updated threshold for picking DGEMM SUP kernel for ZEN4.

AMD-Internal: [CPUPL-5912]
Change-Id: Ic12a1a48bfa59af26cc17ccfa47a2a33fadde1f6
2024-11-29 03:19:16 -05:00
Shubham Sharma
f2320a1fef Enabled DGEMM row major kernel for ZEN4
- Merged ZEN4 and ZEN5 DGEMM 8x24 kernel.
- Replaced 32x6 kernel with 8x24. Now same
  kernel is used for ZEN4 and ZEN5.
- Blocksizes have been tuned for genoa only.
- DGEMM kernel for DTRSM native code path
  is replaced with 8x24 kernel.
- Enabled alpha scaling during packing for ZEN4.
- ZEN4 8x24 kernel has been removed.

AMD-Internal: [CPUPL-5912]
Change-Id: I89a16a7e3355af037d21d453aabf53c5ecccb754
2024-11-29 08:18:48 +00:00
Edward Smyth
82bdf7c8c7 Code cleanup: Copyright notices
- Standardize formatting (spacing etc).
- Add full copyright to cmake files (excluding .json)
- Correct copyright and disclaimer text for frame and
  zen, skx and a couple of other kernels to cover all
  contributors, as is commonly used in other files.
- Fixed some typos and missing lines in copyright
  statements.

AMD-Internal: [CPUPL-4415]
Change-Id: Ib248bb6033c4d0b408773cf0e2a2cda6c2a74371
2024-08-05 15:35:08 -04:00
Varaganti, Kiran
145e706992 Fixed auxiliary cache block sizes for Native and SUP DGEMM kernels for ZEN4 and ZEN5 configs.
Auxiliary blocksize values for cache blocksizes are interpreted as the maximum cache blocksizes. The maximum cache blocksizes are a convenient and portable way of smoothing performance of the level-3 operations when computing with a matrix operand that is just slightly larger than a multiple of the preferred cache blocksize in that dimension. In these "edge cases," iterations run with highly sub-optimal blocking. We can address this problem by merging the "edge case" iteration with the second-to-last iteration, such that the cache blocksizes are slightly larger--rather than significantly smaller--than optimal. The maximum cache blocksizes allow the developer to specify the maximum size of this merged iteration; if the edge case causes the merged iteration to exceed this maximum, then the edge case is not merged and instead it is computed upon in separate (final) iteration. (https://github.com/flame/blis/blob/master/docs/ConfigurationHowTo.md).
      In bli_cntx_init_zen4 and zen5 - auxiliary blocksize for KC was less than primary blocksize. These are fixed.
      Code-cleanup of the files bli_family_zen4, zen5.h" Removed unused constants.
Thanks to Igor Kozachenko <igork@berkeley.edu> for pointing out these two bugs.

Change-Id: I44fc564d5d91cb978d062c413e70751aeaa07f2c
2024-08-05 10:29:43 +05:30
Mangala V
0a4f9d5ac1 Removed -fno-tree-loop-vectorize from kernel flags
- This change in made in MAKE build system.
- Removed -fno-tree-loop-vectorize from global kernel flags,
  instead added it to lpgemm specific kernels only.
- If this flag is not used , then gcc tries to auto
  vectorize the code which results in usages of
  vector registers, if the auto vectorized function
  is using intrinsic then the total numbers of vector
  registers used by intrinsic and auto vectorized
  code becomes more than the registers
  available in machine which causes read and writes
  to stack, which is causing regression in lpgemm.
- If this flag is enabled globally, then the files which
  do not use any intrinsic code do not get auto
  vectorized.
- To get optimal performance for both blis and lpgemm,
  this flag is enabled for lpgemm kernels only.

Previous commit (75df1ef218) contains
similar changes on cmake build system

AMD-Internal: [CPUPL-5544]

Change-Id: I796e89f3fb2116d64c3a78af2069de20ce92d506
2024-08-02 09:40:06 -04:00
Shubham Sharma
0d95fcf20c Revert "DGEMM Native AVX512 updates"
This reverts commit f378fc57b5.

Reason for revert: Causing Failure

AMD-Internal: [CPUPL-5262]
Change-Id: I15860eabf2461fae3d0f7cedd436d4db2df5b82f
2024-08-02 07:32:28 -04:00
Ruchika Ashtankar
92fbd04238 DGEMM SUP Optimizations for Turin
- Introduced a new 24x8 column preferred DGEMM sup kernel for zen5.
- A prefetch logic is modified compared to zen4 24x8 sup kernels.
- Earlier, next panel of A is prefetched into L2 cache,
  which is now modified to prefetching the second next column
  of the current panel of A into L1 cache.
- B and C prefetches are enabled and unchanged.
- Tuned MC, KC and NC block sizes for new kernel.

AMD-Internal: [CPUPL-5262]
Change-Id: If933537e50f43f5560e0fe18a716aa1e36ced64d
2024-08-02 04:00:51 -04:00
Ruchika Ashtankar
5760e06100 Threshold tuning for DGEMM SUP for zen5
- New Decision threshold constants are added to decide between
double precision sup vs native dgemm code-path for zen5 processors.
- The decision is based on the values of m, n and k.

AMD-Internal: [CPUPL-5262]
Change-Id: I87b8ff9eb603d6fda0875e000f7ab83b22d22040
2024-08-02 11:34:32 +05:30
Shubham Sharma.
f378fc57b5 DGEMM Native AVX512 updates
- In the initial patch - for m, n non-multiple of MR and NR
  respectively we are calling bli_dgemm_ker_var2. Now we have
  implemented macro-kernel for these fringe cases as well.
- Replaced RBP register with R11 in the macro-kernel.
- Retuned MC, KC and NC with these new changes.
  This will result in better performance for matrix sizes
  like m=4000 or greater when running on single thread.


AMD-Internal: [CPUPL-5262]
Change-Id: I66c111ceb7feee776703339680d57e8d6d5c809a
2024-07-31 12:23:34 -04:00
Shubham Sharma
16c56e0101 Added 24x8 triangular kernels for DGEMMT SUP
- In order to reuse 24x8 AVX512 DGEMM SUP kernels,
   24x8 triangular AVX512 DGEMMT SUP kernels are added.
 - Since the LCM of MR(24) and NR(8) is 24, therefore the diagonal
   pattern repeats every 24x24 block of C. To cover this 24x24 block,
   3 kernels are needed for one variant of DGEMMT. A total of 6
   kernels are needed to cover both upper and lower variants.
 - In order to maximize code reuse, the 24x8 kernels are broken
   into two parts, 8x8 diagonal GEMM and 16x8 full GEMM. The 8x8
   diagonal GEMM is computed by 8x8 diagonal kernel, and 16x8
   full GEMM part is computed by 24x8 DGEMM SUP kernel.
 - Changes are made in framework to enable the use of these kernels.

AMD-Internal: [CPUPL-5338]
Change-Id: I8e7007031e906f786b0c4fe12377ee439075207a
2024-07-22 12:02:30 -04:00
Vignesh Balasubramanian
b48e864e82 AVX512 optimizations for DAXPBYV API
- Implemented AVX512 computational kernel for DAXPBYV
  with optimal unrolling. Further implemented the other
  missing kernels that would be required to decompose
  the computation in special cases, namely the AVX512
  DADDV and DSCAL2V kernels.

- Updated the zen4 and zen5 contexts to ensure any query
  to acquire the kernel pointer for DAXPBYV returns the
  address of the new kernel.

- Added micro-kernel units tests to GTestsuite to check
  for functionality and out-of-bounds reads and writes.

AMD-Internal: [CPUPL-5406][CPUPL-5421]
Change-Id: I127ab21174ddd9e6de2c30a320e62a8b042cbde6
2024-07-22 11:32:19 +05:30
Shubham Sharma
75df1ef218 Removed -fno-tree-loop-vectorize from kernel flags
- This change in made in CMAKE build system only.
- Removed -fno-tree-loop-vectorize from global kernel flags,
  instead added it to lpgemm specific kernels only.
- If this flag is not used , then gcc tries to auto
  vectorize the code which results in usages of
  vector registers, if the auto vectorized function
  is using intrinsics then the total numbers of vector
  registers used by intrinsic and auto vectorized
  code becomes more than the registers
  available in machine which causes read and writes
  to stack, which is causing regression in lpgemm.
- If this flag is enabled globally, then the files which
  do not use any intrinsic code do not get auto
  vectorized.
- To get optimal performance for both blis and lpgemm,
  this flag is enabled for lpgemm kernels only.

Change-Id: I14e5c18cd53b058bfc9d764a8eaf825b4d0a81c4
2024-07-19 00:49:52 -04:00
Arnav Sharma
4aa66f108e Added CSCALV AVX512 Kernel
- Added CSCALV kernel utilizing the AVX512 ISA.

- Added function pointers for the same to zen4 and zen5 contexts.

- Updated the BLAS interface to invoke respective CSCALV kernels based
  on the architecture.

- Added UKR tests for bli_cscalv_zen_int_avx512( ... ).

AMD-Internal: [CPUPL-5299]
Change-Id: I189d87a1ec1a6e30c16e05582dcb57a8510a27f3
2024-07-15 07:17:43 -04:00
Shubham Sharma.
a7744361e4 DGEMM optimizations for Turin Classic
- Introduced new 8x24 macro kernels.
   - 4 new kernels are added for beta 0, beta 1, beta -1
      and beta N.
   - IR and JR loop moved to ASM region.
   - Kernels support row major storage scheme.
   - Prefetch of current micro panel of C is enabled.
   - Kernel supports negative offsets for A and B matrices.
 - Moved alpha scaling from DGEMM kernel to B pack kernel.
 - Tuned blocksizes for new kernel.
 - Added support for alpha scaling in 24xk pack kernel.
 - Reverted back to old b_next computation
   in gemm_ker_var2.
 - BugFix in 8x24 DGEMM kernel for beta 1,
   comparsion for jmp conditions was done using integer
   instructions, which caused beta 1 path to never be taken.
   Fixed this by changing the comparsion to double.

AMD-Internal: [CPUPL-5262]
Change-Id: Ieec207eea2a164603c8a8ea88e0b1d3095c29a3f
2024-07-09 07:53:27 -04:00
Hari Govind S
627bf0b1ba Implemented Multithreading and Enabled AVX512 Kernel for ZAXPY API
-  Replaced 'bli_zaxpyv_zen_int5' kernel with optimised
   'bli_zaxpyv_zen_int_avx512' kernel for zen4 and
   zen5  config.

-  Implemented multithreading support and AOCL-dynamic
   for ZAXPY API.

-  Utilized 'bli_thread_range_sub' function to achieve
   better work distribution and avoid false sharing.

AMD-Internal: [CPUPL-5250]
Change-Id: I46ad8f01f9d639e0baa78f4475d6e86458d8069b
2024-07-09 01:29:53 -04:00
mkadavil
a5c4a8c7e0 Int4 B matrix reordering support in LPGEMM.
Support for reordering B matrix of datatype int4 as per the pack schema
requirements of u8s8s32 kernel. Vectorized int4_t -> int8_t conversion
implemented via leveraging the vpmultishiftqb instruction. The reordered
B matrix will then be used in the u8s8s32o<s32|s8> api.

AMD-Internal: [SWLCSG-2390]
Change-Id: I3a8f8aba30cac0c4828a31f1d27fa1b45ea07bba
2024-06-24 07:55:34 -04:00
Shubham Sharma.
580282e655 DGEMM optimizations for Turin Classic
- Introduced new 8x24 row preferred kernel for zen5.
  - Kernel supports row/col/gen
    storage schemes.
  - Prefetch of current panel of A and C
    are enabled.
  - Prefetch of next panel of B is enabled.
  - Kernel supports negative offsets for A and B
    matrices.
- Cache block tuning is done for zen5 core.

AMD-Internal: [CPUPL-5262]
Change-Id: I058ea7e1b751c20c516d7b27a1f27cef96ef730f
2024-06-17 05:18:49 -04:00
Hari Govind S
61d0f3b873 Additional optimisations on COPYV API
-  Reduced number of jump operations in AVX512
   assembly kernel for SCOPYV, DCOPYV and ZCOPYV.

-  Fixed memory test failure for bli_zcopyv_zen_int_avx512
   kernel.

-  Replaced existing AVX2 COPYV intrinsic kernels in
   bli_cntx_init_zen5.c with AVX512 assembly kernels.

Change-Id: Idc11601b526d6d82cfbdf63af2fd331918b31159
2024-05-10 07:22:04 -04:00
Arnav Sharma
cb27fad49c ZSCALV AVX512 Kernel
- Implemented ZSCALV kernel utilizing AVX512 intrinsics.

- Gtestsuite: Added ukr tests for the new kernel.

AMD-Internal: [CPUPL-5012]
Change-Id: I75c7f4448ddd60b0f9afa53936eed37f5f99eeb2
2024-05-08 11:55:13 -04:00
Arnav Sharma
1dbeee4d19 ZDOTV AVX512 Kernel with MT Support
- Added AVX512 kernel for ZDOTV.

- Multithreaded both ZDOTC and ZDOTU with AOCL_DYNAMIC support.

AMD-Internal: [CPUPL-5011]
Change-Id: I56df9c07ab3b8df06267a99835b088dcada81bd8
2024-05-08 04:54:05 -04:00
Mangala V
e6cc2a3e22 ZGEMMT SUP Optimizations for AVX512
Existing Design:
 - GEMM AVX2 kernel performs computation and updates temporary C buffer
 - Portion of temporary C buffer is copied to output C buffer
   based on UPLO parameter
 - For diagonal blocks, using GEMM kernels is not efficient

New Design: Implemented in current patch when UPLO='L'
 - GEMMT kernel used for computation, temporary buffer is not required.
 - Only required elements are computed using mask load store for all
   fringe cases
 - Exception: AVX2 code path is used when storage format is RRC, CRR, CRC

- AOCL-Dynamic is added based on dimension
- Check for AVX platform is added in SUP interface, It returns to
  native implementation if hardware doesnot support AVX platform
- SUP ref_var2m is expanded for dcomplex datatype to avoid condition
  check which exists for double datatype

AMD_Internal: [CPUPL-5006]

Change-Id: I3e21404b732b8f2df9cbdba394303752fdf36286
2024-05-07 23:00:29 +05:30
Shubham Sharma
b70347d0d4 DGEMMT SUP Optimizations for AVX512
- In DGEMMT SUP AVX2 code path, traingular kernels
  are added in order to avoid temporary C buffer.
- Since these kernels did not exist for AVX512,
  AVX2 kernels were being used in GEMMT.
- AVX512 triangular GEMM kernel has been added
  to make sure that AVX512 kernels can be used without
  creating a temporary buffer.
- This kernel is added only for Lower variant of GEMMT,
   for upper variant of DGEMMT, temporary C buffer is
   created, full GEMM kernel is called on temporary C and
   traingular region from temporary C is copied to C
   buffer.

AMD-Internal: [CPUPL-4881]
Change-Id: Id70645f79ae078ab9a7006e83d328505f1fae8a9
2024-05-03 05:11:11 -04:00
Vignesh Balasubramanian
53cb83d0cc AVX512 optimizations for ZGEMV API with no-transpose case
- Implemented AVX512 kernels for handling the calls to ZGEMV
  with no-transpose to A matrix.

- This includes the ZAXPYF, ZAXPYV and ZSETV kernels.
  The set of ZAXPYF kernels include those with fuse-factor 8
  (main kernel), 4 and 2(fringe kernels).

- Updated the bli_zgemv_unf_var2( ... ) function to set
  the function pointers to these kernels, based on the
  configuration. Further added the call to ZSETV at this
  layer in case beta is 0.

AMD-Internal: [CPUPL-4974]
Change-Id: Iee4b724719e49023138bb16479765be44d677cd9
2024-05-03 07:04:47 +00:00
Edward Smyth
2450a1813b BLIS: Implement zen5 sub-configuration
Implement full support for zen5 as a separate BLIS sub-configuration
and code path within amdzen configuration family.

AMD-Internal: [CPUPL-3518]
Change-Id: Iaa5096e0b83bf0f0c3fd1c41e601ccd29bda3c09
2024-04-12 07:26:31 -04:00