Add whole decoding line to max_iter plot

src/thesis/chapters/4_decoding_under_dems.tex

@@ -1167,7 +1167,13 @@ reimplementation in Rust to achieve higher simulation speeds due to
 the compiled nature of the language.
 We reimplemented both the window splitting and the decoders themselves.
 
-% Simulation setup
+% Global experimental setup
+%   - Code
+%   - # SE rounds
+%   - Noise model
+%   - Per-round LER as figure of merit
+%   - Detector definition
+%   - # simulated error frames
 
 We chose to carry out our simulations on \ac{bb} codes, as they have
 recently emerged as particularly promising candidates for practical
@@ -1194,13 +1200,60 @@ generated by simulating at least $200$ logical error events.
 \subsection{Belief Propagation}
 \label{subsec:Belief Propagation}
 
-% Intro
+% Local experimental setup
+%   - BP variant
 
-We begin our investigation by using \ac{bp} with no further
+We began our investigation by using \ac{bp} with no further
 modifications as the inner decoder.
 We chose the min-sum variant of \ac{bp} due to its low computational complexity.
 
-% Whole decoding as a lower bound on the error rate
+% [Thread] Get impression for max gain
+%   - More global = better -> Compare windowed vs. whole
+
+% [Description] Figure 4.8
+%   - Parameters
+%     - # BP iterations
+%     - W,F
+%     - Physical error rates
+%     - Windowed (cold start) vs whole decoding
+%     - (?) Semilog y axis
+%   - Figure description
+%     - TODO:
+
+% [Interpretation] Figure 4.8
+%   - Larger window -> better, because more global decoding
+%   - Diminishing returns as the window becomes larger
+%   - As expected, whole works best
+
+% [Thread] First comparison with warm start
+%    - Compare performance of warm start to cold start
+
+% [Description] Figure 4.9
+%   - Parameters
+%     - # BP iterations
+%     - W,F
+%     - Physical error rates
+%     - Warm vs cold start
+%   - Figure description
+%     - TODO:
+
+% [Interpretation] Figure 4.9
+%   - Generally better performance with warm start, as expected
+%   - It is surprising that warm start performs better than whole
+
+% [Thread] Warm start is better than whole due to more effective iterations
+
+% [Description] Figure 4.10
+%   - Parameters
+%     - # BP iterations
+%     - W,F
+%     - Physical error rates
+%     - Warm vs cold start
+%   - Figure description
+%     - TODO:
+
+% [Interpretation] Figure 4.10
+%   -
 
 We initially wanted to gain an impression for the performance gain we could
 expect from a modification to the sliding-window decoding procedure.
@@ -1529,6 +1582,15 @@ though the process is less global.
 
                     \addlegendentryexpanded{$W = \W$}
                 }
+
+                \addplot+[mark=*, solid, mark options={fill=black}, black]
+                table[
+                    col sep=comma, x=max_iter,
+                    y=LER_per_round,
+                ]
+                {res/sim/max_iter/SyndromeMinSumDecoder/p_0.0025/LERs.csv};
+
+                \addlegendentry{Whole}
             \end{axis}
         \end{tikzpicture}
 

src/thesis/copy_sim_results.sh

@@ -129,6 +129,24 @@ sp="/-\|"
 #     done
 # done
 
+# Copy whole BP over max iter. results
+
+echo -e "\rCopying whole over max_iter simulation results..."
+echo -n ' '
+for decoder in "SyndromeMinSumDecoder"; do
+    for p in 0.001 0.0025 0.004; do
+        SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bp,decoder.class_name=${decoder},simulation.phy_err_rate=${p}/"
+        LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+        SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+        DEST_DIR="res/sim/max_iter/${decoder}/p_${p}/"
+        mkdir -p ${DEST_DIR}
+        DEST_FILE="${DEST_DIR}/LERs.csv"
+        cp ${SRC_FILE} ${DEST_FILE}
+        post_process_LERs ${DEST_FILE}
+        printf "\b${sp:i++%${#sp}:1}"
+    done
+done
+
 # # Copy BPGD decimation passing
 #
 # echo -e "\rCopying BPGD param exploration results..."
@@ -151,20 +169,20 @@ sp="/-\|"
 
 # Copy BPGD with decimation info passing over max iter. results
 
-echo -e "\rCopying BPGD over max. iter. results..."
-echo -n ' '
-for pass_soft_info in "True" "False"; do
-    for F in 1 2 3; do
-        for W in 3 4 5; do
-            SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bpgd_pass_channel,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.pass_soft_info=${pass_soft_info},simulation.phy_err_rate=0.0025,system.F=${F},system.W=${W}/"
-            LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
-            SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
-            DEST_DIR="res/sim/max_iter/WindowingSyndromeSpaGdDecoderPassDecimation/p_0.0025/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
-            mkdir -p ${DEST_DIR}
-            DEST_FILE="${DEST_DIR}/LERs.csv"
-            cp ${SRC_FILE} ${DEST_FILE}
-            post_process_LERs ${DEST_FILE}
-            printf "\b${sp:i++%${#sp}:1}"
-        done
-    done
-done
+# echo -e "\rCopying BPGD over max. iter. results..."
+# echo -n ' '
+# for pass_soft_info in "True" "False"; do
+#     for F in 1 2 3; do
+#         for W in 3 4 5; do
+#             SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bpgd_pass_channel,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.pass_soft_info=${pass_soft_info},simulation.phy_err_rate=0.0025,system.F=${F},system.W=${W}/"
+#             LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#             SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#             DEST_DIR="res/sim/max_iter/WindowingSyndromeSpaGdDecoderPassDecimation/p_0.0025/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
+#             mkdir -p ${DEST_DIR}
+#             DEST_FILE="${DEST_DIR}/LERs.csv"
+#             cp ${SRC_FILE} ${DEST_FILE}
+#             post_process_LERs ${DEST_FILE}
+#             printf "\b${sp:i++%${#sp}:1}"
+#         done
+#     done
+# done

src/thesis/res/sim/max_iter/SyndromeMinSumDecoder/p_0.001/LERs.csv

@@ -0,0 +1,8 @@
+max_iter,num_trials,LER,LER_per_round,num_errors
+32,10528,0.0354293313069908,0.0030015014232951387,372.99999999999915
+128,68422,0.0029230364502645,0.00024391332035389457,199.99999999999764
+256,100000,0.00184,0.00015346279666106355,184.0
+512,100000,0.00122,0.00010172355962756452,122.0
+1024,100000,0.00084,7.002696447200307e-05,84.0
+2048,100000,0.00052,4.33436645435048e-05,51.99999999999999
+4096,100000,0.00042,3.5006739308451884e-05,42.0

src/thesis/res/sim/max_iter/SyndromeMinSumDecoder/p_0.0025/LERs.csv

@@ -0,0 +1,8 @@
+max_iter,num_trials,LER,LER_per_round,num_errors
+32,5264,0.3575227963525836,0.03619728900635699,1882.0
+128,5264,0.1118920972644376,0.00983977212107956,588.9999999999995
+256,5264,0.0818768996960486,0.007093372523371166,430.99999999999983
+512,5264,0.0645896656534954,0.005548714177492475,339.9999999999998
+1024,5264,0.0524316109422492,0.004477957765848362,275.9999999999998
+2048,5264,0.0442629179331307,0.0037655941776483237,233.0
+4096,10528,0.0361892097264437,0.0030669771276242708,380.99999999999926

src/thesis/res/sim/max_iter/SyndromeMinSumDecoder/p_0.004/LERs.csv

@@ -0,0 +1,8 @@
+max_iter,num_trials,LER,LER_per_round,num_errors
+32,5264,0.8651215805471124,0.15375677320993897,4554.0
+128,5264,0.5987841945288754,0.0732807818579091,3152.0000000000005
+256,5264,0.5184270516717325,0.05907464062706547,2729.0
+512,5264,0.4591565349544073,0.04992921073125611,2417.0
+1024,5264,0.4209726443768997,0.04451268995716784,2216.0
+2048,5264,0.3865881458966565,0.03990837706831185,2035.0
+4096,5264,0.3563829787234042,0.036054914686007855,1875.9999999999995