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@@ -46,56 +46,6 @@ Please have a look at the [wiki](https://github.com/bassoy/ttm/wiki) page for mo
 * Requires the tensor elements to be contiguously stored in memory.
 * Element types must be an arithmetic type suporting multiplication and addition operator
 
-## Experiments
-
-The experiments were carried out on a Intel Xeon Gold 6248R Xeon processor with 24 cores running at  a base frequency of 3 GHz.
-The source code has been compiled with GCC v10.2 using the highest optimization level `-O3` and `-march=native`, `-pthread` and `-fopenmp`. 
-Parallel execution has been accomplished using GCC’s implementation of the OpenMP v4.5 specification. 
-We have used the `gemv` and `gemm` implementation of the Intel MLK library v2024. 
-The benchmark results of each of the following functions are the average of 10 runs.
-
-The comparison includes three state-of-the-art libraries that implement three different approaches. 
-* [TCL](https://github.com/springer13/tcl) (v0.1.1 ) implements the TTGT approach. 
-* [TBLIS](https://github.com/devinamatthews/tblis) ( v1.0.0 ) implements the GETT approach.
-* [EIGEN](https://bitbucket.org/eigen/eigen/src/default/) ( v3.3.7 ) executes the tensor-times-matrix in-place.
-
-The experiments were carried out with asymmetrically-shaped and symmetrically-shaped tensors in order to provide a comprehensive test coverage where
-the tensor elements are stored according to the first-order storage format.
-The tensor order of the asymmetrically- and symmetrically-shaped tensors have been varied from `2` to `10` and `2` to `7`, respectively.
-The contraction mode `q` has also been varied from `1` to the tensor order.
-
-### Symmetrically-Shaped Tensors
-
-**TTM** has been executed with parameters `tlib::execution::blas`, `tlib::slicing::large` and `tlib::loop_fusion::all`
-
-<table>
-<tr>
-<td><img src="https://github.com/bassoy/ttm/blob/master/misc/symmetric_throughput_single_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-<td><img src="https://github.com/bassoy/ttm/blob/master/misc/symmetric_speedup_single_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-</tr>
-<tr> 
-<td> <img src="https://github.com/bassoy/ttm/blob/master/misc/symmetric_throughput_double_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-<td> <img src="https://github.com/bassoy/ttm/blob/master/misc/symmetric_speedup_double_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-</tr>
-</table>
-
-### Asymmetrically-Shaped Tensors
-
-**TTM** has been executed with parameters `tlib::execution::blas`, `tlib::slicing::small` and `tlib::loop_fusion::all`
-
-<table>
-<tr>
-<td><img src="https://github.com/bassoy/ttm/blob/master/misc/nonsymmetric_throughput_single_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-<td><img src="https://github.com/bassoy/ttm/blob/master/misc/nonsymmetric_speedup_single_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-</tr>
-<tr> 
-<td> <img src="https://github.com/bassoy/ttm/blob/master/misc/nonsymmetric_throughput_double_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-<td> <img src="https://github.com/bassoy/ttm/blob/master/misc/nonsymmetric_speedup_double_precision.png" alt="Drawing" style="width: 250px;"/> </td>
-</tr>
-</table>
-
-
-
 ## Example 
 ```cpp
 /*main.cpp*/