diff --git a/Rust/Savina/src/parallelism/Apsp.lf b/Rust/Savina/src/parallelism/Apsp.lf
new file mode 100644
index 00000000..c71099ef
--- /dev/null
+++ b/Rust/Savina/src/parallelism/Apsp.lf
@@ -0,0 +1,280 @@
+/**
+ * Copyright (C) 2020 TU Dresden
+ *
+ * This benchmark implements a parallel all pairs shortest path algorithm. In
+ * order to split the workload, the large input matrix of size graph_size x
+ * graph_size is split into smaller blocks of size block_size x block_size. Each of
+ * the worker reactors (ApspFloydWarshallBlock) processes one of these blocks.
+ * The worker reactors are organized in the same matrix pattern, replication the
+ * structure of the blocks within the large input matrix. Each of the workers
+ * operates on its local block data, and sends results to all other workers in
+ * the same column or in the same row. The data from the neighbors is then used
+ * to compute the next intermediate result and to update the local state
+ * accordingly.
+ *
+ * @author Christian Menard
+ * @author Hannes Klein
+ * @author Johannes Hayeß
+ */
+
+target Rust {
+    build-type : Release,
+    cargo-features: [ "cli" ],
+    rust-include: [ "../lib/matrix.rs", "../lib/pseudo_random.rs"],
+};
+
+import BenchmarkRunner from "../lib/BenchmarkRunner.lf";
+
+reactor ApspFloydWarshallBlock(
+    bank_index: usize(0),
+    row_index: usize(0),
+    graph_size: usize(300),
+    block_size: usize(50),
+    dimension: usize(6)
+) {
+
+    state bank_index(bank_index);
+    state row_index(row_index);
+    state graph_size(graph_size);
+    state block_size(block_size);
+    state dimension(dimension);
+
+    state num_neighbors: usize({=2 * (dimension - 1)=});
+    state row_offset: usize({=row_index * block_size=}); // row offset of the block of this reactor
+    state col_offset: usize({=bank_index * block_size=}); // column offset of the block of this reactor
+
+    state k: usize(0); // iteration counter
+    state reportedFinish: bool(false);
+
+    input start: Matrix<u64>;
+
+    input[dimension] frow_row: Matrix<u64>;
+    input[dimension] frow_col: Matrix<u64>;
+
+    output toNeighbors: Matrix<u64>;
+    output finished: unit;
+
+    logical action notify_neighbors: Matrix<u64>;
+
+    preamble {=
+        use crate::matrix::Matrix;
+
+        fn get_element_at(
+            row: usize,
+            col: usize,
+            row_ports: &Multiport<Matrix<u64>>,
+            col_ports: &Multiport<Matrix<u64>>,
+            ctx: &ReactionCtx,
+            block_size: usize,
+            row_index: usize,
+            bank_index: usize,
+        ) -> u64 {
+            let dest_row = row / block_size;
+            let dest_col = col / block_size;
+            let local_row = row % block_size;
+            let local_col = col % block_size;
+
+            if dest_row == row_index {
+                *ctx.get_ref(&row_ports[dest_col])
+                   .unwrap()
+                   .get(local_row, local_col)
+            } else if dest_col == bank_index {
+                *ctx.get_ref(&col_ports[dest_row])
+                    .unwrap()
+                    .get(local_row, local_col)
+            } else {
+                panic!("Error: unexpected target location ({},{})", dest_col, dest_row);
+            }
+
+        }
+    =}
+
+    // @label block_start
+    reaction(start) -> notify_neighbors {=
+        // reset local state
+        self.k = 0;
+        self.reportedFinish = false;
+
+        // start execution
+        let matrix = ctx.get_ref(start).unwrap().clone();
+        ctx.schedule_with_v(notify_neighbors, Some(matrix), Asap);
+    =}
+
+    reaction(notify_neighbors) -> toNeighbors {=
+        //notify all neighbors
+        ctx.set(toNeighbors, ctx.use_ref_opt(notify_neighbors, Clone::clone).unwrap());
+    =}
+
+    reaction(frow_row, frow_col) -> notify_neighbors, finished {=
+        // do nothing if complete
+        if self.k == self.graph_size {
+            return;
+        }
+
+        // perform computation
+        let mut matrix: Matrix<u64> = Matrix::new(self.block_size, self.block_size);
+        let bs = self.block_size;
+        let ri = self.row_index;
+        let bi = self.bank_index;
+
+        for i in 0..self.block_size {
+            for j in 0..self.block_size {
+                let gi = self.row_offset + i;
+                let gj = self.col_offset + j;
+
+                let result = get_element_at(gi, self.k, frow_row, frow_col, &ctx, bs, ri, bi) 
+                           + get_element_at(self.k, gj, frow_row, frow_col, &ctx, bs, ri, bi);
+                matrix.set(i, j, result.min(get_element_at(gi, gj, frow_row, frow_col, &ctx, bs, ri, bi)));
+            }
+        }
+
+       // increment iteration count
+       self.k += 1;
+
+       if self.k == self.graph_size {
+            if self.bank_index == 0 && self.row_index == 0 {
+                debug!("{}", matrix);
+            }
+            ctx.set(finished, ());
+        }
+
+        // send the result to all neighbors in the next iteration
+        ctx.schedule_with_v(notify_neighbors, Some(matrix), Asap);
+    =}
+}
+
+reactor ApspRow(
+    bank_index: usize(0),
+    block_size: usize(50),
+    num_nodes: usize(300),
+    dimension: usize(6),
+    dimension_sq: usize(36)
+) {
+    preamble {=
+        use crate::matrix::Matrix;
+    =}
+
+    input start: Matrix<u64>;
+    output[dimension] finished: unit;
+
+    input[dimension_sq] frow_col: Matrix<u64>;
+    output[dimension] to_col: Matrix<u64>;
+
+    blocks = new[dimension] ApspFloydWarshallBlock(
+        row_index=bank_index,
+        block_size=block_size,
+        graph_size=num_nodes,
+        dimension=dimension
+    );
+
+    // connect all blocks within the row
+    (blocks.toNeighbors)+ -> blocks.frow_row;
+
+    // block output to all column neighbours
+    blocks.toNeighbors -> to_col;
+    // block input from all column neighbours
+    frow_col -> interleaved(blocks.frow_col);
+
+    // broadcast the incoming matrix to all blocks
+    (start)+ -> blocks.start;
+    // collect and forward finished signals from all blocks
+    blocks.finished -> finished;
+}
+
+reactor ApspMatrix(
+    block_size: usize(50),
+    num_nodes: usize(300),
+    dimension: usize(6),
+    dimension_sq: usize(36)
+) {
+    preamble {=
+        use crate::matrix::Matrix;
+    =}
+    input start: Matrix<u64>;
+    output[dimension_sq] finished: unit;
+
+    rows = new[dimension] ApspRow(block_size=block_size, num_nodes=num_nodes, dimension=dimension, dimension_sq=dimension_sq);
+
+    // broadcast the incoming matrix to all rows
+    (start)+ -> rows.start;
+    // collect and forward finished signals from all blocks
+    rows.finished -> finished;
+
+    (rows.to_col)+ -> rows.frow_col;
+}
+
+main reactor (
+    num_iterations: usize(12),
+    max_edge_weight: usize(100),
+    block_size: usize(50),
+    num_nodes: usize(300)
+) {
+    state num_iterations(num_iterations);
+    state max_edge_weight(max_edge_weight);
+    state block_size(block_size);
+    state num_nodes(num_nodes);
+
+    state num_blocks_finished: usize(0);
+
+    runner = new BenchmarkRunner(num_iterations=num_iterations);
+    matrix = new ApspMatrix(
+        block_size=block_size,
+        num_nodes=num_nodes,
+        dimension={=num_nodes / block_size=},
+        dimension_sq={=(num_nodes / block_size)*(num_nodes / block_size)=}
+    );
+
+    reaction(startup) {=
+        print_benchmark_info("ApspBenchmark");
+        print_args!(
+            "num_iterations",
+            self.num_iterations,
+            "max_edge_weight",
+            self.max_edge_weight,
+            "num_nodes",
+            self.num_nodes,
+            "block_size",
+            self.block_size
+        );
+        print_system_info();
+    =}
+
+    // @label dostart
+    reaction(runner.start) -> matrix.start {=
+        // reset local state
+        self.num_blocks_finished = 0;
+        let graph_data = generate_graph(self.num_nodes, self.max_edge_weight);
+        // start execution
+        ctx.set(matrix__start, graph_data);
+    =}
+
+    reaction (matrix.finished) -> runner.finished {=
+        self.num_blocks_finished += matrix__finished.iterate_set().count();
+        let dimension = self.num_nodes / self.block_size;
+        if self.num_blocks_finished == dimension * dimension {
+            ctx.set(runner__finished, ());
+        }
+    =}
+
+    preamble {=
+        use crate::matrix::Matrix;
+        use crate::{print_args,reactors::benchmark_runner::{print_system_info, print_benchmark_info}};
+        use crate::pseudo_random::PseudoRandomGenerator;
+        use std::os::raw::c_long;
+
+        fn generate_graph(n: usize, w: usize) -> Matrix<u64> {
+            let mut random = PseudoRandomGenerator::from(n as c_long);
+            let mut local_data: Matrix<u64> = Matrix::new(n, n);
+
+            for i in 0..n {
+                for j in (i+1)..n {
+                    let r = u64::from(random.next_in_range(0..w as c_long)) + 1;
+                    local_data.set(i, j, r);
+                    local_data.set(j, i, r);
+                }
+            }
+
+            local_data
+        }
+    =}
+}
diff --git a/runner/conf/benchmark/savina_parallelism_apsp.yaml b/runner/conf/benchmark/savina_parallelism_apsp.yaml
index e379d542..6b3a383d 100644
--- a/runner/conf/benchmark/savina_parallelism_apsp.yaml
+++ b/runner/conf/benchmark/savina_parallelism_apsp.yaml
@@ -46,3 +46,13 @@ targets:
       num_workers: ["-D", "numNodes=<value>"]
       block_size: ["-D", "blockSize=<value>"]
       max_edge_weight: ["-D", "maxEdgeWeight=<value>"]
+  lf-rust:
+    copy_sources:
+      - "${bench_path}/Rust/Savina/src/lib"
+      - "${bench_path}/Rust/Savina/src/parallelism"
+    lf_file: "parallelism/Apsp.lf"
+    binary: "apsp"
+    run_args:
+      block_size: ["--main-block-size", "<value>"]
+      max_edge_weight: ["--main-max-edge-weight", "<value>"]
+      num_workers: ["--main-num-nodes", "<value>"]