Commit Graph

791 Commits

Author SHA1 Message Date
Edward Smyth
4eabb5cd2e SCALV alpha=zero BLAS compliance
SCALV is used directly by BLAS, CBLAS and BLIS scal{v} APIs but
also within many other APIs to handle special cases. In general
it is preferred to use SETV when alpha=0, but BLAS and CBLAS
continue to multiple all vector element by alpha. This has
different behaviour for propagating NaNs or Infs.

Changes in this commit:
- Standardize early returns from SCALV reference and optimized
  kernels.
- User supplied N<0 is handled at the top level API layer. Use
  negative values of N in kernel calls to signify that SETV
  should _not_ be used when alpha=0. This should only be
  required in SCALV.
- Include serial threshold in zdscal (as in dscal) to reduce
  overhead for small problem sizes.
- Code tidying to make different variants more consistent.
- More standardization of tests in SCALV gtestsuite programs.
- Remove scalv_extreme_cases.cpp as it is now redundant.

AMD-Internal: [CPUPL-4415]
Change-Id: I42e98875ceaea224cc98d0cdfe0133c9abc3edae
(cherry picked from commit a07e041b1f)
2024-09-20 01:05:03 -04:00
Vignesh Balasubramanian
86798b03ae Fixed compiler warnings due to prefetch in AVX2 and AVX512 kernels
- Added explicit typecast to the pointers that are passed
  to the _mm_prefetch( ... ) intrinsic, to avoid compiler
  warnings.

AMD-Internal: [CPUPL-4415]
Change-Id: I1c1398b7b5abe81848d33cb6df107f7f077588ea
2024-09-16 06:33:21 -04:00
Meghana Vankadari
5855874df3 Developed all WoQ kernels for bf16s4f32o<f32|bf16>
Description:

1. Written 6x64 main and other fringe kernels for WoQ where scaling s4
   weights into bf16 performed in the kernel itself to reduce bandwidth.

2. These kernels are performing better compared to bf16 weights when m
   is small and n is large.

3. Established a threshold to do quantization support at packing of
   B (KCXNC) level or WoQ kernel level.

Change-Id: I4f8265b8b58c276ff2590cc948d1f920aa0bb289
(cherry picked from commit 5120f98e12)
2024-09-10 08:31:53 -04:00
varshav2
c47470c0bd Add TransA and TransB support for F32F32F32oF32
- Added support for TransA and transB in f32f32of32 APIs
 - Modified the GEMV case(m == 1) to support PACKB feature
 - Redirecting the operations to GEMM instead of GEMV in case of n == 1
   conditions, with storage scheme r/transA and c/transB to avoid the
   packing errors which would lead to failures in computation.

Change-Id: I0eb8c31485af4e33c53fd36b5e5788d75d3a67a9
2024-09-09 22:15:07 +05:30
Meghana Vankadari
64ca52b5b8 Bug fix in WOQ kernel for m=4 case.
- Updated pre_op_off computation for nr0 < NR cases.
- Fixed warnings in bench file.

Change-Id: Iae30fa84b6b47ebd94ab05d2139056aee24546d7
(cherry picked from commit 687abe4c96)
2024-09-05 09:31:58 +00:00
Meghana Vankadari
1007f00632 Added bf16s4f32 kernels to handle m=4 cases
Details:
- In WOQ, if m = 4, special case kernels are added where
  s4->bf16 conversion happens inside the compute kernel and
  packing is avoided. For all other cases, B matrix is
  dequantized and packed at KC loop level and native bf16
  kernels are re-used at compute level.
- Fixes in bench to avoid accuracy failures when datatype of
  output is bf16.

Change-Id: Ie8db42da536891693d5e82a5336b66514a50ccb2
(cherry picked from commit 2e1cc2f14a)
2024-09-05 06:25:28 +00:00
Deepak Negi
1a388b1e1d Element wise operations API for float(f32) input matrix in LPGEMM.
This API supports applying element wise operations (eg: post-ops) on a
float(f32) input matrix to get an output matrix of the same (float(f32)).

Change-Id: I387a544f0d33d2231f5f6a92e212f17b1103dd24

AMD Internal: [SWLCSG-2947]

Change-Id: I387a544f0d33d2231f5f6a92e212f17b1103dd24
2024-08-27 08:17:29 -04:00
Chandrashekara K R
09d5021a30 CMake: Enabled ADDON(aocl_gemm) feature for Windows.
1. Updated datatype from __int64_t to int64_t. Since
   __int64_t was not defined for Windows
2. Updated CMake build system to build lpgemm on windows

Change-Id: I5fc5ed93ecc54e4a9931b7b40b790d37c7ead4b8
(cherry picked from commit 2ff0125f11)
2024-08-26 02:03:29 -04:00
Vignesh Balasubramanian
a29efd12b1 Bugfix : Fixed memory accesses in AVX512 SGEMMSUP RD kernels
- Bug: Among the list of AVX512 SGEMMSUP RD kernels, the ones handling
  m_fringe = 3 had incorrect usage of ZMM on a vector-load instruction
  that strictly needed YMMs.

- Further updated the existing micro-kernel test cases to simulate
  these issues and validate the fix.

AMD-Internal: [CPUPL-5353]
Change-Id: Id86e60ce36bb9f8433a1a203cfe0b8c6347df2c1
2024-08-20 02:22:16 -04:00
Vignesh Balasubramanian
f8f070f6ec Fixing compiler warnings when exporting internal BLIS kernels
- Added the attribute to export symbols, in the header file that
  contains the L1 kernel declarations. This attribute was previously
  added as part of the kernel definitions.

AMD-Internal: [CPUPL-4415]
Change-Id: I375246f47d53c220f885644f9b75c7d7991ae710
2024-08-20 02:11:11 -04:00
Meghana Vankadari
b1c046ef1d Added LPGEMV(n=1) kernels for s8s8s32os32|s8 and s8s8s16os16|s8 APIs
- When n=1, reorder of B matrix is avoided to efficiently
  process data. A dot-product based kernel is implemented to
  perform gemv when n==1.

AMD-Internal: [SWLCSG-2354]
Change-Id: I6b73dfddd9a15e7b914d031646a1d913a7ab4761
2024-08-20 11:17:24 +05:30
Edward Smyth
7fff7b4026 Code cleanup: Miscellaneous fixes
- Delete unused cmake files.
- Add guards around call to bli_cpuid_is_avx2fma3_supported
  in frame/3/bli_l3_sup.c, currently assumes that non-x86
  platforms will not use bli_gemmtsup.
- Correct variable in frame/base/bli_arch.c on non-x86
  builds.
- Add guards around omp pragma to avoid possible gcc
  compiler warning in kernels/zen/2/bli_gemv_zen_int_4.c.
- Add missing registers in clobber list in
  kernels/zen4/1/bli_dotv_zen_int_avx512.c.
- Add gtestsuite ERS_IIT tests for TRMV, copied from TRSV.
- Correct calls to cblas_{c,z}swap in gtestsuite.
- Correct test name in ddotxf gtestsuite program.

AMD-Internal: [CPUPL-4415]
Change-Id: I69ad56390017676cc609b4d3aba3244a2df6a6b5
2024-08-06 06:56:01 -04:00
Edward Smyth
89f52a6df5 Code cleanup: spelling corrections
Corrections for spelling and other mistakes in code comments
and doc files.

AMD-Internal: [CPUPL-4500]
Change-Id: I33e28932b0e26bbed850c55602dee12fd002da7f
2024-08-05 16:18:51 -04:00
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
Nallani Bhaskar
e712673ab7 Peformance fixes for gcc compiler in fringe kernels
Description:
1. GCC avoiding loading b into registers in m fringe
   kenrels of int8 kernels. Instead gcc generating
   fma with memory as an operand for B input.

2. This is causing performance regression for larger n
   where each fma needs to load the input from memory
   again and again.

3. This is observed with gcc but not with clang.

4. Inserted dummy shuffle instructions for b data to
   further explicitly tell compiler that b needs to be in
   registers.

   AMD-Internal: SWLCSG-2948

Change-Id: Ibbf186fe6569e6265e2c2bb4ec3141ef323ea3e6
2024-08-05 14:31:22 -04:00
Edward Smyth
591a3a7395 Code cleanup: file formats and permissions
- Remove execute file permission from source and make files.
- dos2unix conversion.
- Add missing eol at end of files.

Also update .gitignore to not exclude build directory but to
exclude any build_* created by cmake builds.

AMD-Internal: [CPUPL-4415]
Change-Id: I5403290d49fe212659a8015d5e94281fe41eb124
2024-08-05 11:52:33 -04:00
mkadavil
9f5fec7713 Matrix MUL op support in element wise operations API for bfloat16.
-Matrix MUL op support added in main as well as fringe bfloat16 element
wise operations kernels.
-Benchmarking/testing framework for the same is added.
-Fixed issues in setting up post-ops node index.

AMD Internal: [SWLCSG-2947, SWLCSG-2953]

Change-Id: Iba7561a6a60df41211efbf06fab1b4900207bcf8
2024-08-05 08:29:42 +05:30
Deepak Negi
80bf6249f0 Matrix MUL post-operation support for float(bf16|f32) LPGEMM APIs.
This post-operation computes C = (beta*C + alpha*A*B) * D, where D
is a matrix with dimensions and data type the same as that of C matrix.

AMD-Internal: [SWLCSG-2953]

Change-Id: Id4df2ca76a8f696cb16edbd02c25f621f9a828fd
2024-08-05 08:25:32 -04:00
Nallani Bhaskar
4c2f436cce Peformance fixes for gcc compiler in fringe kernels
Description:
1. GCC avoiding loading b into registers in m fringe
   kenrels of int8 kernels. Instead gcc generating
   fma with memory as an operand for B input.

2. This is causing performance regression for larger n
   where each fma needs to load the input from memory
   again and again.

3. This is observed with gcc but not with clang.

4. Inserted dummy shuffle instructions for b data to
   further explicitly tell compiler that b needs to be in
   registers.

5. Moved packb_s4_to_bf16 under JIT macro to resovle
   compilation  issue with gcc version < 11.2

AMD-Internal: SWLCSG-2948

Change-Id: I5bd1bad7ad129e0dde91ed78d49a4ede3bff456a
2024-08-05 08:13:06 -04:00
mkadavil
f040ba617f Element wise operations API for bfloat16 input matrix in LPGEMM.
-This API supports applying element wise operations (eg: post-ops) on a
bfloat16 input matrix to get an output matrix of the same(bfloat16) or
upscaled data type (float).
-Benchmarking/testing framework for the same is added.

AMD Internal: SWLCSG-2947

Change-Id: I43f1c269be1a1997d4912d8a3a97be5e5f3442d2
2024-08-05 07:17:08 -04:00
Arnav Sharma
0a5c057475 DGEMV Optimizations for Tiny Sizes
- Added reference kernel for dgemv that handles computation for tiny
  sizes (m < 8 && n < 8).

- The reference kernel, bli_dgemv_zen_ref( ... ), supports both
  row/column storage schemes as well as transpose and no transpose
  cases.

- Added additional unit-tests for functional verification.

AMD-Internal: [CPUPL-5098]
Change-Id: I66fdf0a40e90bdb3fed40152c45ab28a17a87ada
2024-08-05 12:19:42 +05:30
Vignesh Balasubramanian
9843bd0317 Tuning the decision logic to choose SUP vs Native for ZGEMM
- Added an additional decision logic to choose between SUP and
  Native paths for zen4 and zen5 micro-architectures, based on
  the input dimensions. This logic has been added to the
  architecture-specific thresholds functions, that are registered
  in the context.

- The decision logic will overrule the discrete thresholds present
  in the zen4 and zen5 contexts.

AMD-Internal: [CPUPL-5547]
Change-Id: I475f19b110064b3b9eef2e03bbdc21f4dd826c03
2024-08-03 19:08:07 +05:30
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
Moripalli Chitra
8b486e8d14 Added new decision logic to choose between 6x8 dgemm kernel vs 24x8 kernel. The decision is based on the values of "m, n and k".
Change-Id: I307ff002797ccef5bd61106b808cecb069b91fd6
2024-08-02 14:18:58 +05:30
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
Vignesh Balasubramanian
4ec2bad744 Updating reduction step of AVX512 DNRM2 API
- Updated the final reduction of partial sums to use scalar accumulation
  entirely, instead of using the _mm512_reduce_add_pd( ... ) intrinsic.
  This will in turn change the associativity and the rounding-off
  pattern in the reduction step.

- Defined a union data-type to do the same, by having a 512-bit
  register and a double-precision array as its members.

- Updated the declaration and usage of the register variable according
  to the union definition, for uniformity.

AMD-Internal: [CPUPL-5472]
Change-Id: I997464a6ec47e4054dca48a000fbd4ac0cfcc679
2024-08-01 17:09:17 +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
Vignesh Balasubramanian
f23b8e636b AVX2 and AVX512 optimizations for DAXPYV
- Removed some of the unrolling factors that affected the
  performance of AVX2 DAXPYV kernel. In addition to improving
  the current performance on sizes compatible to single-threaded
  runs, this will now perform better for tiny sizes as well
  since the overhead to reach the computation is less.

- Updated the vector partitioning logic, by using
  bli_thread_range_sub( ... ), which ensures that there is no
  false sharing among multiple threads.

- Updated the AOCL-DYNAMIC logic for the API, to include thresholds
  or zen4 and zen5 micro-architectures.

AMD-Internal: [CPUPL-5514]
Change-Id: Iee9edddac685334213cd6694421ab3df3547e930
2024-07-31 09:24:36 -04:00
Hari Govind S
e2e95a09b0 Fixing missing registers in end_asm for copyv APIs
-  Added the missing registers in end_asm for scopy,
   dcopy and zcopy APIs.

-  Removed unnecessary registers from end_asm for scopy
   and dcopy APIs.

-  Corrected mistakes in the comments.

Change-Id: I5ebe2ff9cb2c72ca7c71a67419281f73462f9498
2024-07-30 15:09:52 +05:30
Meghana Vankadari
d5b4d3aa5e Fixing control flow in aocl_gemm_bf16s4f32of32|bf16
- Fixed framework of bf16s4f32of32 API to correct
  pointer updations.
- Modified pre_op structure to exclude pre-op-offset.
  Now offset is passed as a separate parameter to the
  scale-pack functions.
- Fixed work-distribution among threads in MT scenario.
- Added Blocksizes and kernel-pointers and verified
  functionality for the new API.

AMD-Internal: [SWLCSG-2943]
Change-Id: I58fece240d62c798c880a2b2b7fa64e560cc753d
2024-07-29 05:12:09 -04:00
Nallani Bhaskar
c6dd7c1b4b Added new API in aocl_gemm to support A bf16 data type and B s4 data type
Description:

1. Added a new API aocl_gemm_bf16s4f32of32 to support
   for WoQ (Weight-only-Quantization) in LLM's

2. The API supports only reordered B matrix of data
   size signed 4 bits (S4).

3. Substracting zero point and multiplying with scale
   on B matrix is performed in packing B.

4. zero point and scale data should be passed by user
   through pre-ops data structure.

5. The API is still in experimental state and NOT tested.

   AMD-Internal: SWLCSG-2943

Change-Id: I10b159b64c2e2aaf39da5462685618ba8cc800ee
2024-07-25 11:59:03 +00:00
Meghana Vankadari
49949f488f Implemented on-the-go pack kernel for s4->bf16
Details:
- To enable Weight-only-Quantization(WOQ) workflow,
  new LPGEMM APIs are added where datatypes are A: bf16,
  B: int4, C: f32/bf16. To support this, B matrix will
  be reordered with type still being int4. New pack
  kernels that packs the reordered B matrix after
  converting the data from int4 to bf16 and applying
  zero-point and scale are added.

AMD-Internal: [SWLCSG-2943]
Change-Id: Iabe23dab607913c0114b97cb2b91248babeaac03
2024-07-25 04:13:05 +05:30
mkadavil
7114376519 New kernels for int4 B matrix reordering following BF16 kernel schema.
-To enable Weight-only-Quantization (WOQ) workflow, new LPGEMM APIs
are required where data types are A:bf16, B:int4 and C:f32/bf16. It
is expected that the BF16 kernels will be reused within this API and
subsequently the B matrix needs to be reordered following the BF16
kernel schema, but with the reordered matrix type still being int4. To
address this, new BF16 reorder kernels enabling the same are added.

AMD-Internal: [SWLCSG-2943]
Change-Id: Ib770ecbf90a3d906deafece94b1a96e0b9412738
2024-07-25 01:10:13 -04:00
Hari Govind S
eacad443e3 Optimization for DCOPY and SCOPY API
-  Replaced "vmovupd" with "vmovups" for "bli_scopyv_zen4_asm_avx512"
   kernel.

-  Optimization of loop unrolling for "bli_dcopyv_zen4_asm_avx512"
   and "bli_scopyv_zen4_asm_avx512" kernels.

-  Replaced existing load balancing algorithm for dcopy API with
   "bli_thread_range_sub" algorithm.

-  Included AOCL-dynamic values for optimial number of threads
   for zen5 architecture.

AMD-Internal: [CPUPL-5238]
Change-Id: Ic82bdfad9478c8f75dc5a3dcfed0df85fbcae957
2024-07-24 08:23:07 -04:00
Arnav Sharma
9583ee2e23 DGEMV Optimizations for NO_TRANSPOSE cases
- Enabled AVX512 DAXPYF kernels for DGEMV var2 for NO_TRANSPOSE cases.

- Added DAXPYF kernels with fuse factors of 2, 4, 6 and 16.

- Added a wrapper for DAXPYF kernels for redirection to kernels with a
  smaller fuse factor than 32.

- Also added UKR tests for the new fused kernels.

AMD-Internal: [CPUPL-5098]
Change-Id: I0b102b67c6c068873393bac0494284f379c253f2
2024-07-24 15:59:36 +05:30
mkadavil
42e539b878 Quantization (scale + zero point) updates/fixes for BF16 LPGEMM api.
-_mm512_cvtpbh_ps intrinsic is not supported in older versions of gcc
(<gcc 12.2) and subsequently throws a compilation error. This is fixed
by replacing this intrinsic with a macro that achieves the bf16 to f32
conversion via shift operations.
-Bug fixes in the vector scale factor load in fringe kernels.

AMD-Internal: [SWLCSG-2945]
Change-Id: I8eac4c4b34b043e7a8116dc465723d8f85b28018
2024-07-23 04:39:14 +05:30
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
Vignesh Balasubramanian
cec9fdcc6e Framework enhancements for ?AXPBYV APIs
- Implemented a new front-end for the BLAS/CBLAS calls
  to ?AXPBYV(BLAS-extension API), that is intended to
  be compiled only on Zen micro-architectures(as per the
  existing build system).

- This new front-end makes the framework lightweight for
  BLAS/CBLAS calls to ?AXPBYV, by directly querying the
  architecture ID and deploying the associated computational
  kernel.

- Further updated the rerouting to other L1 kernels based
  on alpha and beta value. This was initially present in
  the Typed-API interface. It has been moved inside the
  respective kernels, and only necessary rerouting is done
  to specific L1 kernels to avoid redundant checks.

AMD-Internal: [CPUPL-5406]
Change-Id: I4af943d477a25dcdab4ee6009ad3dfa6a5c2b37e
2024-07-18 10:06:31 -04:00
mkadavil
d37c91dffa Quantization (scale + zero point) support for BF16 LPGEMM api.
-Quantization of f32 to bf16 (bf16 = (f32 * scale_factor) + zero_point)
instead of just type conversion in aocl_gemm_bf16bf16f32obf16.
-Support for multiple scale/sum/matrix_add/bias post-ops in a single
LPGEMM api call.
-Post-ops mask related fixes in lpgemv kernels .
-Additional scale post-ops sanity checks.

AMD-Internal: [SWLCSG-2945]
Change-Id: I3b35cc413c176bb50bfdbd6acd4839a5ba7e94bb
2024-07-18 05:32:51 -04:00
Hari Govind S
38824244d5 Implementation of AXPYF Kernels for DTRSV
-  Implemented two new axpyf kernels for fused factors 8 and 12
   by manually unrolling the loops. Used to achieve better performance
   in var2 case.

AMD-Internal: [CPUPL-5184]
Change-Id: I40d2930d003c6ce90323b5c8a52564563d1f23f5
2024-07-16 06:23:01 -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
vignbala
236d092656 AVX512 optimizations for ZGEMM to handle k = 1 cases
- Implemented bli_zgemm_16x4_avx512_k1_nn( ... ) AVX512 kernel to
  be used as part of BLAS/CBLAS calls to ZGEMM. The kernel is built
  for handling the GEMM computation with inputs having k = 1,
  with the transpose values being N(for column-major) and T(for
  row-major).

- Updated the zgemm_blis_impl( ... ) layer to query the architecture
  ID and invoke the AVX2 or AVX512 kernel accordingly.

- Added API level tests for accuracy and code-coverage, as well as
  micro-kernel tests for verifying functionality and out-of-bounds
  memory accesses.

AMD-Internal: [CPUPL-5249]
Change-Id: Id1f8bebff3e0da83c7febe86299564fd658b2e84
2024-07-09 07:07:24 -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
Edward Smyth
2ee46a3a3a Merge commit 'cfa3db3f' into amd-main
* commit 'cfa3db3f':
  Fixed bug in mixed-dt gemm introduced in e9da642.
  Removed support for 3m, 4m induced methods.
  Updated do_sde.sh to get SDE from GitHub.
  Disable SDE testing of old AMD microarchitectures.
  Fixed substitution bug in configure.
  Allow use of 1m with mixing of row/col-pref ukrs.

AMD-Internal: [CPUPL-2698]
Change-Id: I961f0066243cf26aeb2e174e388b470133cc4a5f
2024-07-08 06:09:11 -04:00
Meghana Vankadari
4e6fa17c08 Bug fix in LPGEMV for INT8 APIs
Details:
- Corrected the usage of vpdpbusd instruction in
  GEMV implementation for INT8 APIs.
- Modified bench to fill matrices with values
  ranging between -5 and +5 whenever the datatype is
  a signed integer.

Change-Id: I457462b888b667d8a34c53de762e9b4aee784ecc
2024-06-27 04:22:04 +05:30
mkadavil
a26c85333a Int4 B matrix reordering support fixes in LPGEMM.
Reordering B matrix of datatype int4 is done as per the pack schema
requirements of u8s8s32 kernel. However for fringe cases, the
matrix pointer increments need to be halved to account for the half
byte size of int4 elements.

AMD-Internal: [SWLCSG-2390]
Change-Id: I22a04c4c8133db6ae6ca0a4d3e86c11aba1e2cdb
2024-06-26 05:39:45 +05:30