Merge pull request #78 from cpmech/remove-intel-dss-solver

Remove Intel DSS

.vscode/c_cpp_properties.json

@@ -11,7 +11,6 @@
         "/usr/local/include/umfpack"
       ],
       "defines": [
-        "WITH_INTEL_DSS",
         "USE_INTEL_MKL"
       ],
       "compilerPath": "/usr/bin/gcc",
@@ -21,4 +20,4 @@
     }
   ],
   "version": 4
-}
+}

.vscode/settings.json

@@ -39,7 +39,6 @@
     "ifort",
     "IIIₛ",
     "ᵢⱼₖₗ",
-    "inteldss",
     "iomp",
     "irhs",
     "jobvl",

README.md

@@ -29,7 +29,7 @@ Next, we recommend looking at the [russell_sparse](https://github.com/cpmech/rus
 Available crates:
 
 - [![Crates.io](https://img.shields.io/crates/v/russell_lab.svg)](https://crates.io/crates/russell_lab) [russell_lab](https://github.com/cpmech/russell/tree/main/russell_lab) Matrix-vector laboratory for linear algebra (with OpenBLAS or Intel MKL)
-- [![Crates.io](https://img.shields.io/crates/v/russell_sparse.svg)](https://crates.io/crates/russell_sparse) [russell_sparse](https://github.com/cpmech/russell/tree/main/russell_sparse) Sparse matrix tools and solvers (with MUMPS, UMFPACK, and Intel DSS)
+- [![Crates.io](https://img.shields.io/crates/v/russell_sparse.svg)](https://crates.io/crates/russell_sparse) [russell_sparse](https://github.com/cpmech/russell/tree/main/russell_sparse) Sparse matrix tools and solvers (with MUMPS and UMFPACK)
 - [![Crates.io](https://img.shields.io/crates/v/russell_stat.svg)](https://crates.io/crates/russell_stat) [russell_stat](https://github.com/cpmech/russell/tree/main/russell_stat) Statistics calculations, probability distributions, and pseudo random numbers
 - [![Crates.io](https://img.shields.io/crates/v/russell_tensor.svg)](https://crates.io/crates/russell_tensor) [russell_tensor](https://github.com/cpmech/russell/tree/main/russell_tensor) Tensor analysis structures and functions for continuum mechanics
 
@@ -365,7 +365,6 @@ fn main() -> Result<(), StrError> {
     - [x] Implement the Compressed Sparse Column format (CSC)
     - [x] Implement the Compressed Sparse Row format (CSC)
     - [x] Improve the C-interface to UMFPACK and MUMPS
-    - [x] Implement the C-interface to Intel DSS
     - [ ] Write the conversion from COO to CSC in Rust
     - [ ] Possibly re-write (after benchmarking) the conversion from COO to CSR
     - [ ] Re-study the possibility of wrapping SuperLU (see deleted branch)

russell_ode/Cargo.toml

@@ -11,6 +11,9 @@ readme = "README.md"
 categories = ["mathematics", "science"]
 keywords = ["differential equations", "numerical methods", "solver"]
 
+[features]
+intel_mkl = ["russell_lab/intel_mkl", "russell_sparse/intel_mkl"]
+
 [dependencies]
 russell_lab = { path = "../russell_lab", version = "0.8" }
 russell_sparse = { path = "../russell_sparse", version = "0.8" }

russell_sparse/Cargo.toml

@@ -13,7 +13,7 @@ keywords = ["matrix", "sparse", "solver"]
 
 [features]
 local_libs = []
-intel_mkl = ["local_libs"]
+intel_mkl = ["local_libs", "russell_lab/intel_mkl"]
 
 [dependencies]
 num-complex = { version = "0.4", features = ["serde"] }

russell_sparse/README.md

@@ -14,7 +14,7 @@ _This crate is part of [Russell - Rust Scientific Library](https://github.com/cp
 
 ## <a name="introduction"></a> Introduction
 
-This crate implements tools for handling sparse matrices and functions to solve large sparse systems using the best libraries out there, such as [UMFPACK (recommended)](https://github.com/DrTimothyAldenDavis/SuiteSparse) and [MUMPS (for very large systems)](https://mumps-solver.org). Optionally, you may want to use the [Intel DSS solver](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2023-2/direct-sparse-solver-dss-interface-routines.html).
+This crate implements tools for handling sparse matrices and functions to solve large sparse systems using the best libraries out there, such as [UMFPACK (recommended)](https://github.com/DrTimothyAldenDavis/SuiteSparse) and [MUMPS (for very large systems)](https://mumps-solver.org).
 
 We have three storage formats for sparse matrices:
 
@@ -26,7 +26,7 @@ Additionally, to unify the handling of the above sparse matrix data structures,
 
 * SparseMatrix: Either a COO, CSC, or CSR matrix
 
-The COO matrix is the best when we need to update the values of the matrix because it has easy access to the triples (i, j, aij). For instance, the repetitive access is the primary use case for codes based on the finite element method (FEM) for approximating partial differential equations. Moreover, the COO matrix allows storing duplicate entries; for example, the triple `(0, 0, 123.0)` can be stored as two triples `(0, 0, 100.0)` and `(0, 0, 23.0)`. Again, this is the primary need for FEM codes because of the so-called assembly process where elements add to the same positions in the "global stiffness" matrix. Nonetheless, the duplicate entries must be summed up at some stage for the linear solver (e.g., MUMPS, UMFPACK, and Intel DSS). These linear solvers also use the more memory-efficient storage formats CSC and CSR. See the [russell_sparse documentation](https://docs.rs/russell_sparse) for further information.
+The COO matrix is the best when we need to update the values of the matrix because it has easy access to the triples (i, j, aij). For instance, the repetitive access is the primary use case for codes based on the finite element method (FEM) for approximating partial differential equations. Moreover, the COO matrix allows storing duplicate entries; for example, the triple `(0, 0, 123.0)` can be stored as two triples `(0, 0, 100.0)` and `(0, 0, 23.0)`. Again, this is the primary need for FEM codes because of the so-called assembly process where elements add to the same positions in the "global stiffness" matrix. Nonetheless, the duplicate entries must be summed up at some stage for the linear solver (e.g., MUMPS, UMFPACK). These linear solvers also use the more memory-efficient storage formats CSC and CSR. See the [russell_sparse documentation](https://docs.rs/russell_sparse) for further information.
 
 This library also provides functions to read and write Matrix Market files containing (huge) sparse matrices that can be used in performance benchmarking or other studies. The [read_matrix_market()] function reads a Matrix Market file and returns a [CooMatrix]. To write a Matrix Market file, we can use the function [write_matrix_market()], which takes a [SparseMatrix] and, thus, automatically convert COO to CSC or COO to CSR, also performing the sum of duplicates. The `write_matrix_market` also writes an SMAT file (almost like the Matrix Market format) without the header and with zero-based indices. The SMAT file can be given to the fantastic [Vismatrix](https://github.com/cpmech/vismatrix) tool to visualize the sparse matrix structure and values interactively; see the example below.
 
@@ -38,7 +38,7 @@ See the documentation for further information:
 
 ## <a name="installation"></a> Installation
 
-This crate depends on `russell_lab`, which, in turn, depends on an efficient BLAS library such as [OpenBLAS](https://github.com/OpenMathLib/OpenBLAS) and [Intel MKL](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2023-2/overview.html). This crate also depends on [UMFPACK](https://github.com/DrTimothyAldenDavis/SuiteSparse), [MUMPS](https://mumps-solver.org), and, optionally, on [Intel DSS](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2023-2/direct-sparse-solver-dss-interface-routines.html).
+This crate depends on `russell_lab`, which, in turn, depends on an efficient BLAS library such as [OpenBLAS](https://github.com/OpenMathLib/OpenBLAS) and [Intel MKL](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2023-2/overview.html). This crate also depends on [UMFPACK](https://github.com/DrTimothyAldenDavis/SuiteSparse) and [MUMPS](https://mumps-solver.org).
 
 [The root README file presents the steps to install the required dependencies.](https://github.com/cpmech/russell)
 
@@ -245,7 +245,7 @@ Also, to reproduce the issue, we need:
 
 ## <a name="developers"></a> For developers
 
-* The `c_code` directory contains a thin wrapper to the sparse solvers (MUMPS, UMFPACK, and Intel DSS)
+* The `c_code` directory contains a thin wrapper to the sparse solvers (MUMPS, UMFPACK)
 * The `build.rs` file uses the crate `cc` to build the C-wrappers
 * The `zscripts` directory also contains following:
     * `memcheck.bash`: Checks for memory leaks on the C-code using Valgrind

russell_sparse/build.rs

@@ -1,6 +1,3 @@
-#[cfg(feature = "intel_mkl")]
-const MKL_VERSION: &str = "2023.2.0";
-
 #[cfg(feature = "local_libs")]
 fn handle_local_libs() {
     // local MUMPS
@@ -42,40 +39,6 @@ fn handle_local_libs() {
     println!("cargo:rustc-link-lib=dylib=umfpack");
 }
 
-#[cfg(feature = "intel_mkl")]
-fn handle_intel_mkl() {
-    // Find the link libs with: pkg-config --libs mkl-dynamic-lp64-iomp
-    cc::Build::new()
-        .file("c_code/interface_intel_dss.c")
-        .include(format!("/opt/intel/oneapi/mkl/{}/include", MKL_VERSION))
-        .define("WITH_INTEL_DSS", None)
-        .compile("c_code_interface_intel_dss");
-    println!(
-        "cargo:rustc-link-search=native=/opt/intel/oneapi/mkl/{}/lib/intel64",
-        MKL_VERSION
-    );
-    println!(
-        "cargo:rustc-link-search=native=/opt/intel/oneapi/compiler/{}/linux/compiler/lib/intel64_lin",
-        MKL_VERSION
-    );
-    println!("cargo:rustc-link-lib=mkl_intel_lp64");
-    println!("cargo:rustc-link-lib=mkl_intel_thread");
-    println!("cargo:rustc-link-lib=mkl_core");
-    println!("cargo:rustc-link-lib=pthread");
-    println!("cargo:rustc-link-lib=m");
-    println!("cargo:rustc-link-lib=dl");
-    println!("cargo:rustc-link-lib=iomp5");
-    println!("cargo:rustc-cfg=with_intel_dss");
-}
-
-#[cfg(not(feature = "intel_mkl"))]
-fn handle_intel_mkl() {
-    cc::Build::new()
-        .file("c_code/interface_intel_dss.c")
-        .compile("c_code_interface_intel_dss");
-}
-
 fn main() {
     handle_local_libs();
-    handle_intel_mkl();
 }

russell_sparse/examples/nonlinear_system_4eqs.rs

@@ -22,7 +22,6 @@ fn main() -> Result<(), StrError> {
     let genie = match opt.genie.to_lowercase().as_str() {
         "mumps" => Genie::Mumps,
         "umfpack" => Genie::Umfpack,
-        "dss" => Genie::IntelDss,
         _ => Genie::Umfpack,
     };
     println!("... solving problem with {:?} ...", genie);