LIBXSMM

https://libxsmm.readthedocs.io/
Admin
LIBXSMM is a library for specialized dense and sparse matrix operations as well as for deep learning...
Tokens:127,011
Snippets:798
Trust Score:9.6
Update:4 weeks ago
Show doc for...
Tokens:
Raw
### Build and install a complete library set

Source: https://libxsmm.readthedocs.io/

Build and install both static and shared libraries by running the install target twice with appropriate flags.

```bash
make PREFIX=/path/to/libxsmm-install STATIC=0 install
make PREFIX=/path/to/libxsmm-install install
```

--------------------------------

### Build SPECFEM example for default CPU host

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Compiles the SPECFEM example for a default CPU host.

```bash
cd sample/specfem
make
```

--------------------------------

### Build and run Hello LIBXSMM with Bazelisk

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Builds and runs the Hello LIBXSMM example using Bazelisk, which boot-straps Bazel. The build command compiles the example and the resulting binary is executed.

```bash
cd /path/to/libxsmm/samples/hello
bazelisk build //...

./bazel-bin/hello

```

--------------------------------

### Install LIBXSMM into workstation sub-directory

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Installs libraries into a sub-directory named workstation/.

```bash
make MNK="5 25" ALPHA=1 BETA=0 PRECISION=1 OPT=3 AVX=1 \
OFFLOAD=1 KNC=1 \
PREFIX=workstation/ install-minimal
```

--------------------------------

### Set environment variables and run torch_example.py

Source: https://libxsmm.readthedocs.io/libxsmm_samples

Commands to set LD_LIBRARY_PATH, OMP_NUM_THREADS, and KMP_AFFINITY, then run the PyTorch example. The example compares nn.Conv1d with the optimized Conv1dOpti layer.

```bash
export LD_LIBRARY_PATH={LIBXSMM_ROOT/lib}           # Set LD_LIBRARY_PATH
export OMP_NUM_THREADS=28                           # Set number of threads
export KMP_AFFINITY=compact,1,0,granularity=fine    # Set KMP affinity

python torch_example.py                             # Run the pytorch example

```

--------------------------------

### Install LIBXSMM with default options

Source: https://libxsmm.readthedocs.io/en/latest

Build and install a complete set of libraries where the generated interface matches both static and shared libraries. This is the recommended command for a general package.

```makefile
make PREFIX=/path/to/libxsmm-install STATIC=0 install
make PREFIX=/path/to/libxsmm-install install

```

--------------------------------

### Install LIBXSMM to a specific location

Source: https://libxsmm.readthedocs.io/

Install the library to a custom directory using the PREFIX variable.

```bash
make MNK="1 2 3 4 5" PREFIX=/path/to/libxsmm-install install
```

--------------------------------

### Run Conv1dOpti example

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Environment configuration and execution commands for running the torch_example.py script.

```bash
export LD_LIBRARY_PATH={LIBXSMM_ROOT/lib}           # Set LD_LIBRARY_PATH
export OMP_NUM_THREADS=28                           # Set number of threads
export KMP_AFFINITY=compact,1,0,granularity=fine    # Set KMP affinity

python torch_example.py                             # Run the pytorch example
```

--------------------------------

### Run multi-threaded specfem example on Haswell

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Run the multi-threaded example from the sample/specfem directory. The command changes to that directory, builds with make OPT=3, and runs with OMP_NUM_THREADS=24.

```bash
cd sample/specfem
make OPT=3; OMP_NUM_THREADS=24 ./specfem.sh

```

--------------------------------

### Install LIBXSMM with PREFIX

Source: https://libxsmm.readthedocs.io/en/latest

Install LIBXSMM to a specific location using PREFIX. The PREFIX and DESTDIR variables are equivalent and can be relative or absolute paths.

```makefile
make MNK="1 2 3 4 5" PREFIX=/path/to/libxsmm-install install

```

--------------------------------

### Run multi-threaded specfem example on Knights Corner

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Run the multi-threaded example from the sample/specfem directory. The command changes to that directory, builds with make FCFLAGS="-O3 -fopenmp -warn" OPT=3 KNC=1, and runs with ./specfem.sh -mic.

```bash
cd sample/specfem
make FCFLAGS="-O3 -fopenmp -warn" OPT=3 KNC=1; ./specfem.sh -mic

```

--------------------------------

### Build LIBXSMM on FreeBSD with gmake

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_compat

Build LIBXSMM under FreeBSD using gmake. For libxsmmext, install OpenMP first with 'sudo pkg install openmp'. Tests may require a LAPACK/BLAS installation unless BLAS=0 is given.

```bash
bash
gmake

```

--------------------------------

### Build SPECFEM example for Knights Corner (KNC)

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Compiles the SPECFEM example for Knights Corner.

```bash
cd sample/specfem
make KNC=1
```

--------------------------------

### Build and run Hello LIBXSMM with GNU Make

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Builds and runs the Hello LIBXSMM example using GNU Make. First builds the library, then the sample, and finally runs the resulting executable.

```bash
cd /path/to/libxsmm
make

cd /path/to/libxsmm/samples/hello
make

./hello

```

--------------------------------

### Build SPECFEM for Knights Corner in two steps

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Two-step build for Knights Corner: first build the library, then the SPECFEM example.

```bash
make MNK="5 25" ALPHA=1 BETA=0 PRECISION=1 OPT=3 AVX=1 OFFLOAD=1 KNC=1
make OPT=3 specfem_mic
```

--------------------------------

### Generator driver examples

Source: https://libxsmm.readthedocs.io/libxsmm_be

Three example invocations of the generator driver program, each with different arguments for dense, dense_asm, and sparse kernels.

```bash
bin/libxsmm_gemm_generator dense foo.c foo 16 16 16 32 32 32 1 1 1 1 hsw nopf DP

```

```bash
bin/libxsmm_gemm_generator dense_asm foo.c foo 16 16 16 32 32 32 1 1 1 1 knl AL2_BL2viaC DP

```

```bash
bin/libxsmm_gemm_generator sparse foo.c foo 16 16 16 32 0 32 1 1 1 1 hsw nopf DP bar.csc

```

--------------------------------

### Build SPECFEM example for Knights Corner via two steps

Source: https://libxsmm.readthedocs.io/libxsmm_samples

Two-step build for Knights Corner: first build LIBXSMM with OFFLOAD=1 KNC=1, then build the specfem_mic target.

```bash
make MNK="5 25" ALPHA=1 BETA=0 PRECISION=1 OPT=3 AVX=1 OFFLOAD=1 KNC=1
make OPT=3 specfem_mic

```

--------------------------------

### Run single-threaded specfem example on Sandy Bridge

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Run the single-threaded example from the sample/specfem directory. The command changes to that directory, builds with make, and runs with OMP_NUM_THREADS=1.

```bash
cd sample/specfem
make; OMP_NUM_THREADS=1 ./specfem.sh

```

--------------------------------

### Install Conv1dOpti extension

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Commands to install the optimized 1D dilated convolutional layer package within an environment containing PyTorch.

```bash
conda activate environment              # Activate anaconda or virtual environment containing PyTorch

cd Conv1dOpti-extension/
python setup.py install                 # Install package
cd ..
```

--------------------------------

### Hello LIBXSMM: C++ matrix multiplication kernel

Source: https://libxsmm.readthedocs.io/en/latest

C++ example that generates and dispatches a matrix multiplication kernel using the libxsmm_mmfunction template. Build with 'make STATIC=0', compile with 'g++ -I/path/to/libxsmm/include hello.cpp -L/path/to/libxsmm/lib -lxsmm -lblas -o hello', and run with 'LD_LIBRARY_PATH=/path/to/libxsmm/lib LIBXSMM_VERBOSE=2 ./hello'. The kernel computes C += Ai * Bi for a batch of matrices.

```cpp
#include <libxsmm.h>
#include <vector>
int main(int argc, char* argv[]) {
  typedef double T;
  int batchsize = 1000, m = 13, n = 5, k = 7;
  std::vector<T> a(batchsize * m * k), b(batchsize * k * n), c(m * n, 0);
  /* C/C++ and Fortran interfaces are available */
  typedef libxsmm_mmfunction<T> kernel_type;
  /* generates and dispatches a matrix multiplication kernel (C++ functor) */
  kernel_type kernel(LIBXSMM_GEMM_FLAG_NONE, m, n, k, 1.0 /*alpha*/, 1.0 /*beta*/);
  assert(kernel);
  for (int i = 0; i < batchsize; ++i) { /* initialize input */
    for (int ki = 0; ki < k; ++ki) {
      for (int j = 0; j < m; ++j) a[i * j * ki] = static_cast<T>(1) / ((i + j + ki) % 25);
      for (int j = 0; j < n; ++j) b[i * j * ki] = static_cast<T>(7) / ((i + j + ki) % 75);
    }
  }
  /* kernel multiplies and accumulates matrices: C += Ai * Bi */
  for (int i = 0; i < batchsize; ++i) kernel(&a[i * m * k], &b[i * k * n], &c[0]);
}

```

--------------------------------

### SMM Benchmark Sample Output

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Example output from running the specialized benchmark script with argument 0, showing performance metrics for the batched (A,B,C) streaming case. The output includes pseudo-performance in FLOPS/cycle, performance in GFLOPS/s, memory bandwidth, and duration.

```bash
$ ./specialized.sh 0
m=32 n=32 k=32 size=87381 memory=2048.0 MB (DP)

Batched (A,B,C)...
        pseudo-perf.: 10.7 FLOPS/cycle
        performance: 23.9 GFLOPS/s
        bandwidth: 11.1 GB/s
        duration: 239 ms
Finished

```

--------------------------------

### Example of verbose test output

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_valid

Shows the output format when LIBXSMM_VERBOSE is set to 4 or higher, displaying the command used for a test.

```text
[...]
LIBXSMM_TARGET: hsw
Registry and code: 13 MB + 8 KB (meltw=1)
Command: ./eltwise_binary_simple 1 0 F32 F32 F32 F32 10 10 10 10 
[...]
```

--------------------------------

### Run SpecFEM single-threaded (Haswell)

Source: https://libxsmm.readthedocs.io/libxsmm_samples

Runs the SpecFEM example with a single thread after building it. The output shows timing results for different loop implementations.

```bash
cd sample/specfem
make; OMP_NUM_THREADS=1 ./specfem.sh

```

```text
===============================================================
average over           15 repetitions
 timing with Deville loops    =   0.1028
 timing with unrolled loops   =   0.1385 / speedup =   -34.73 %
 timing with LIBXSMM dispatch =   0.1408 / speedup =   -37.02 %
 timing with LIBXSMM prefetch =   0.1327 / speedup =   -29.07 %
 timing with LIBXSMM static   =   0.1151 / speedup =   -11.93 %
===============================================================

```

--------------------------------

### Initialize and Finalize LIBXSMM Library

Source: https://libxsmm.readthedocs.io/en/latest

Call libxsmm_init() to pay setup cost at a specific point and avoid lazy initialization overhead. Optionally call libxsmm_finalize() to de-initialize the library and free internal memory; the library also deallocates resources at program exit.

```c
/** Initialize the library; pay for setup cost at a specific point. */
void libxsmm_init(void);
/** De-initialize the library and free internal memory (optional). */
void libxsmm_finalize(void);

```

--------------------------------

### Set PKG_CONFIG_PATH and query libxsmm link flags

Source: https://libxsmm.readthedocs.io/en/latest

Use pkg-config to ease linking with LIBXSMM. Set PKG_CONFIG_PATH to the lib directory and run pkg-config libxsmm --libs to get the necessary link flags.

```bash
export PKG_CONFIG_PATH=/path/to/libxsmm/lib
pkg-config libxsmm --libs

```

--------------------------------

### Static Specialization with M, N, K

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_tune

Builds LIBXSMM with statically specialized matrix multiplication kernels for the given M, N, and K values. The example generates a set of (M,N,K) triplets in a loop-nest relationship.

```make
make M="2 4" N="1" K="$(echo $(seq 2 5))"

```

--------------------------------

### Install Conv1dOpti extension

Source: https://libxsmm.readthedocs.io/libxsmm_samples

Commands to activate an environment and install the Conv1dOpti package. Requires PyTorch installed in an anaconda or virtual environment and GCC version 8.3.0 or higher.

```bash
conda activate environment              # Activate anaconda or virtual environment containing PyTorch

cd Conv1dOpti-extension/
python setup.py install                 # Install package
cd ..

```

--------------------------------

### Install MinGW dependencies with pacman

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_compat

Installs required packages for building LIBXSMM in the native MinGW environment using MSYS2. The command installs make, python, diffutils, GCC, GCC Fortran, and OpenBLAS.

```bash
pacman -S msys/make msys/python msys/diffutils \
  mingw64/mingw-w64-x86_64-gcc mingw64/mingw-w64-x86_64-gcc-fortran \
  mingw64/mingw-w64-x86_64-openblas

```

--------------------------------

### Run C sample with wrapper script

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Executes the C sample via the wrapper script with out-of-place transpose kind and matrix size 20000x20000. The output shows the matrix dimensions, leading dimensions, size in MB, bandwidth, and duration.

```bash
$ ./transpose.sh o 20000
m=20000 n=20000 ldi=20000 ldo=20000 size=3052MB (double, out-of-place)
        bandwidth: 18.8 GB/s
        duration: 159 ms

```

--------------------------------

### Build LIBXSMM with default settings (make STATIC=0 and make)

Source: https://libxsmm.readthedocs.io/en/latest

Generates the interface and builds the static library. By default, STATIC=1 is activated; use STATIC=0 to build shared libraries. Run either or both commands.

```bash
make STATIC=0
make

```

--------------------------------

### Build and compile libxsmm and samples

Source: https://libxsmm.readthedocs.io/libxsmm_samples

Commands to compile the LIBXSMM library and the magazine samples. Run from the project root, then inside the samples/magazine directory.

```shell
cd libxsmm; make
cd samples/magazine; make

```

--------------------------------

### Run basic tests

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_valid

Executes the basic test suite using make.

```bash
make tests
```

--------------------------------

### Verbosity Level Functions

Source: https://libxsmm.readthedocs.io/libxsmm_aux

Functions to get and set the verbosity level.

```APIDOC
## libxsmm_get_verbosity

### Description
Returns the current verbosity level.

### Syntax
```c
int libxsmm_get_verbosity(void);
```

### Parameters
None.

### Returns
- **int** - The current verbosity level.
```

```APIDOC
## libxsmm_set_verbosity

### Description
Sets the verbosity level. The environment variable LIBXSMM_VERBOSE corresponds to this function.

### Syntax
```c
void libxsmm_set_verbosity(int level);
```

### Parameters
- **level** (int) - Required - The verbosity level to set.
```

--------------------------------

### Clean OpenTuner database

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Removes the OpenTuner database file to start a fresh tuning experiment.

```bash
rm -rf opentuner.db

```

--------------------------------

### libxsmm_ptr_dmm and libxsmm_ptr_smm: C-address of kernel handles

Source: https://libxsmm.readthedocs.io/en/latest/fortran/sourcefile/libxsmm.f.html

Functions to get C pointer to the handle of LIBXSMM_DMMFUNCTION and LIBXSMM_SMMFUNCTION arrays.

```Fortran
        FUNCTION libxsmm_ptr_dmm(a)
          TYPE(LIBXSMM_DMMFUNCTION), INTENT(IN), TARGET :: a(:)
          TYPE(LIBXSMM_DMMFUNCTION), POINTER :: p
          TYPE(C_PTR) :: libxsmm_ptr_dmm
          p => a(LBOUND(a,1)); libxsmm_ptr_dmm = C_LOC(p%handle)
        END FUNCTION
        FUNCTION libxsmm_ptr_smm(a)
          TYPE(LIBXSMM_SMMFUNCTION), INTENT(IN), TARGET :: a(:)
          TYPE(LIBXSMM_SMMFUNCTION), POINTER :: p
          TYPE(C_PTR) :: libxsmm_ptr_smm
          p => a(LBOUND(a,1)); libxsmm_ptr_smm = C_LOC(p%handle)
        END FUNCTION
```

--------------------------------

### libxsmm_init()

Source: https://libxsmm.readthedocs.io/en/latest/fortran/interface/libxsmm_init.html

Initializes the LIBXSMM library. This subroutine must be called before using other LIBXSMM functions.

```APIDOC
## libxsmm_init()

### Description
Initializes the LIBXSMM library. This subroutine must be called before using other LIBXSMM functions.

### Method
subroutine

### Endpoint
libxsmm_init

### Parameters
#### Arguments
_None_

### Request Example
```fortran
call libxsmm_init()
```

### Response
#### Success Response
No return value.

#### Response Example
```
(no output)
```
```

--------------------------------

### Basic dispatch and invoke pattern for TPP

Source: https://libxsmm.readthedocs.io/libxsmm_tpp

Shows the generic sequence: create operand shape, define a kernel function pointer, dispatch (JIT compile or retrieve), prepare parameters, and invoke. The placeholder `<op>` must be replaced with the operation group. The parameter preparation step is incomplete (noted with `?.?`) and requires filling with actual parameters.

```c
// Get the shape of the operands to build the right operand
op_shape = libxsmm_create_<op>_shape(matrix dimensions, leading dimensions, data types);

// Define a new kernel
libxsmm_xsmmfunction kernel = {NULL};

// Dispatch (JIT compile or retrieve the previously compiled function)
kernel.<op> = libxsmm_dispatch_<op>(op_shape, FLAGS);

// Prepare the execution parameters
libxsmm_<op>_param op_param;
op_param.?.? = op parameters

// Call the kernel
kernel.<op>(&op_param);

```

--------------------------------

### libxsmm_ptr_b0/b1/b2: C-address of char arrays

Source: https://libxsmm.readthedocs.io/en/latest/fortran/sourcefile/libxsmm.f.html

Functions to get C pointer for CHARACTER(C_CHAR) arrays: scalar, 1D, and 2D.

```Fortran
        !> Determines the C-address of the given array.
        FUNCTION libxsmm_ptr_b0(a)
          CHARACTER(C_CHAR), INTENT(IN), TARGET :: a
          TYPE(C_PTR) :: libxsmm_ptr_b0
          libxsmm_ptr_b0 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_b1(a)
          CHARACTER(C_CHAR), INTENT(IN), TARGET :: a(*)
          TYPE(C_PTR) :: libxsmm_ptr_b1
          libxsmm_ptr_b1 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_b2(a)
          CHARACTER(C_CHAR), INTENT(IN) :: a(:,:)
          TYPE(C_PTR) :: libxsmm_ptr_b2
          libxsmm_ptr_b2 = libxsmm_ptr_b1(a)
        END FUNCTION
```

--------------------------------

### libxsmm_ptr_j0/j1/j2: C-address of int8 arrays

Source: https://libxsmm.readthedocs.io/en/latest/fortran/sourcefile/libxsmm.f.html

Functions to get C pointer for INTEGER(C_INT8_T) arrays: scalar, 1D, and 2D.

```Fortran
        !> Determines the C-address of the given array.
        FUNCTION libxsmm_ptr_j0(a)
          INTEGER(C_INT8_T), INTENT(IN), TARGET :: a
          TYPE(C_PTR) :: libxsmm_ptr_j0
          libxsmm_ptr_j0 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_j1(a)
          INTEGER(C_INT8_T), INTENT(IN), TARGET :: a(*)
          TYPE(C_PTR) :: libxsmm_ptr_j1
          libxsmm_ptr_j1 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_j2(a)
          INTEGER(C_INT8_T), INTENT(IN) :: a(:,:)
          TYPE(C_PTR) :: libxsmm_ptr_j2
          libxsmm_ptr_j2 = libxsmm_ptr_j1(a)
        END FUNCTION
```

--------------------------------

### Run C sample with manual OpenMP affinity

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Runs the C sample with manual OpenMP affinity settings and verbose output (LIBXSMM_VERBOSE=2). The output shows the same matrix parameters and performance metrics, plus a registry line indicating the tcopy kernel was used.

```bash
LIBXSMM_VERBOSE=2 KMP_AFFINITY=balanced,granularity=fine,1 \
./transpose o 20000
m=20000 n=20000 ldi=20000 ldo=20000 size=3052MB (double, out-of-place)
        bandwidth: 21.1 GB/s
        duration: 141 ms

Registry: 20 MB (gemm=0 mcopy=0 tcopy=1)

```

--------------------------------

### libxsmm_ptr_w0/w1/w2: C-address of short arrays

Source: https://libxsmm.readthedocs.io/en/latest/fortran/sourcefile/libxsmm.f.html

Functions to get C pointer for INTEGER(C_SHORT) arrays: scalar, 1D, and 2D.

```Fortran
        !> Determines the C-address of the given array.
        FUNCTION libxsmm_ptr_w0(a)
          INTEGER(C_SHORT), INTENT(IN), TARGET :: a
          TYPE(C_PTR) :: libxsmm_ptr_w0
          libxsmm_ptr_w0 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_w1(a)
          INTEGER(C_SHORT), INTENT(IN), TARGET :: a(*)
          TYPE(C_PTR) :: libxsmm_ptr_w1
          libxsmm_ptr_w1 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_w2(a)
          INTEGER(C_SHORT), INTENT(IN) :: a(:,:)
          TYPE(C_PTR) :: libxsmm_ptr_w2
          libxsmm_ptr_w2 = libxsmm_ptr_w1(a)
        END FUNCTION
```

--------------------------------

### Control verbosity level (libxsmm_get_verbosity, libxsmm_set_verbosity)

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_aux

Get or set the verbosity level. The environment variable LIBXSMM_VERBOSE corresponds to libxsmm_set_verbosity.

```c
int libxsmm_get_verbosity(void);
void libxsmm_set_verbosity(int level);

```

--------------------------------

### Build and run magazine benchmarks

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Builds the LIBXSMM library and the magazine sample, then runs the benchmark script. The benchmark streams matrix operands by default; edit magazine.h to change STREAM_A, STREAM_B, and STREAM_C. Runs single-threaded by default; use `make OMP=1` to parallelize the batch.

```shell
cd libxsmm; make
cd samples/magazine; make

```

```shell
./benchmark.sh

```

--------------------------------

### Build LIBXSMM with default options

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_samples

Compiles the library with static kernels for matrix sizes (5,25), (25,5), and (5,5).

```bash
make MNK="5 25" ALPHA=1 BETA=0
```

--------------------------------

### Run basic tests with make tests

Source: https://libxsmm.readthedocs.io/libxsmm_valid

Runs the basic test suite for LIBXSMM. Use this to verify a default build.

```bash
make tests

```

--------------------------------

### libxsmm_ptr_l0/l1/l2: C-address of long long arrays

Source: https://libxsmm.readthedocs.io/en/latest/fortran/sourcefile/libxsmm.f.html

Functions to get C pointer for INTEGER(C_LONG_LONG) arrays: scalar, 1D, and 2D.

```Fortran
        !> Determines the C-address of the given array.
        FUNCTION libxsmm_ptr_l0(a)
          INTEGER(C_LONG_LONG), INTENT(IN), TARGET :: a
          TYPE(C_PTR) :: libxsmm_ptr_l0
          libxsmm_ptr_l0 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_l1(a)
          INTEGER(C_LONG_LONG), INTENT(IN), TARGET :: a(*)
          TYPE(C_PTR) :: libxsmm_ptr_l1
          libxsmm_ptr_l1 = C_LOC(a)
        END FUNCTION
        FUNCTION libxsmm_ptr_l2(a)
          INTEGER(C_LONG_LONG), INTENT(IN) :: a(:,:)
          TYPE(C_PTR) :: libxsmm_ptr_l2
          libxsmm_ptr_l2 = libxsmm_ptr_l1(a)
        END FUNCTION
```

--------------------------------

### libxsmm_xrelease

Source: https://libxsmm.readthedocs.io/en/latest/fortran/lists/procedures.html

Releases registered data associated with a key. This can be used to free memory before program termination, for example when reusing a key with a larger value.

```APIDOC
## libxsmm_xrelease

### Description
Releases registered data associated with a key. This can be used to free memory before program termination, for example when reusing a key with a larger value.

### Method
Interface
```

--------------------------------

### Verbose output from failing test

Source: https://libxsmm.readthedocs.io/libxsmm_valid

Example output from a failing test when running with LIBXSMM_VERBOSE=4. The termination message shows the LIBXSMM_TARGET, registry size, and the command that was launched.

```text
[...]
LIBXSMM_TARGET: hsw
Registry and code: 13 MB + 8 KB (meltw=1)
Command: ./eltwise_binary_simple 1 0 F32 F32 F32 F32 10 10 10 10 
[...]

```

--------------------------------

### Invoke generator driver for dense_asm kernel

Source: https://libxsmm.readthedocs.io/en/latest/libxsmm_be

Example invocation of the generator driver for a dense_asm kernel with DP precision, knl architecture, and AL2_BL2viaC prefetch strategy.

```bash
bin/libxsmm_gemm_generator dense_asm foo.c foo 16 16 16 32 32 32 1 1 1 1 knl AL2_BL2viaC DP

```
Tokens:
Raw