%% GPU vs CPU Comparison Test for DP_Fiber % This script runs the fiber simulation with and without GPU acceleration % and compares the numerical results. % clear; clc; %% Setup (same as gpu_processing_dpfiber.m but simplified) s.wavelengthplan = calcWavelengthPlan(4, 400e9, 1310); link_length = 10; s.pmd = 0.1; s.gamma = 0.0023; s.M = 4; fsym = 112e9; fdac = 2*fsym; fadc = 120000000000; s.random_key = 1; % Laser / Modulator vbias_rel = 0.5; u_pi = 4.6; vbias = -vbias_rel*u_pi; laser_linewidth = 0e6; % DB Stuff duob_mode = db_mode.no_db; rcalpha = 0.05; Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rc","pulselength",16,"alpha",rcalpha); s.chirpalpha = 0; s.p_launch = 3; s.p = "co"; N = numel(s.wavelengthplan); switch s.p case "co" pol_rot = 100.*ones(1,N); d_local = 0; case "pair" pol_rot = repmat([100,100,0,0],1,N/4); d_local = 0; case "alt" pol_rot = repmat([100,0,100,0],1,N/4); d_local = 0; case "seg" pol_rot = 100.*ones(1,N); d_local = 3; otherwise error('Unknown fwm_mitigation_technique: %s', string(s.p)); end f_plan = physconst('lightspeed')./(s.wavelengthplan.*1e-9); margin = 5e12; f_span = (max(f_plan)+margin)-(min(f_plan)-margin); f_nyq = f_span/2; kover = 4; upsample_required = f_nyq./(fdac*kover/2); upsample_pow = 2^nextpow2(upsample_required); s.f_opt = fdac*kover*upsample_pow; s.f_opt_nyq = s.f_opt/2; %% TX per channel for l = 1:N [Digi_sig,Symbols{l},Tx_bits{l}] = PAMsource( ... "fsym",fsym,"M",s.M,"order",15,"useprbs",0, ... "fs_out",fdac, ... "applyclipping",0,"clipfactor",1.5, ... "applypulseform",1,"pulseformer",Pform, ... "randkey",s.random_key+l, ... "mrds_code",0,"mrds_blocklength",512,"duobinary_mode",duob_mode ... ).process(); Lp_awg = Filter('filtdegree',3,"f_cutoff",56e9,"fs",fdac*kover, ... "filterType",filtertypes.gaussian,"active",true); El_sig = AWG("fdac",fdac,"f_cutoff",fsym,"lpf_active",1,"kover",kover, ... "bit_resolution",6,"upsampling_method","samplehold","precomp_sinc_rolloff",0, ... "H_lpf",Lp_awg,"dac_max",0.6,"dac_min",-0.6).process(Digi_sig); clear Digi_sig El_sig = El_sig.normalize("mode","oneone"); scaling = 0.6*(u_pi/2-abs(vbias-u_pi/2)); El_sig = El_sig .* scaling; Eml_out = EML("mode",eml_mode.im_cosinus,"power",3,"fsimu",El_sig.fs, ... "lambda",s.wavelengthplan(l),"bias",vbias,"u_pi",u_pi, ... "linewidth",laser_linewidth,"randomkey",s.random_key+l,"alpha",s.chirpalpha).process(El_sig); clear El_sig signal_cell{l} = Polarization_Controller("mode","rot_power","desired_power",pol_rot(l)).process(Eml_out); clear Eml_out Lp_awg end disp('Signal generated for all channels.'); %% WDM mux + launch Opt_sig_wdm = Optical_Multiplex("fs_in",fdac*kover,"fs_out",upsample_pow*fdac*kover, ... "lambda_center",1310,"random_key",0,"filtype",1,"B",120e9).process(signal_cell); Opt_sig_wdm = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power", ... "amplification_db",s.p_launch+10*log10(N)).process(Opt_sig_wdm); % Save input for both runs Opt_sig_input = Opt_sig_wdm; segment_length = 1; nSegments = link_length/segment_length; if abs(nSegments - round(nSegments)) > 1e-12 error('fiber_length_km=%g must be an integer multiple of segment_length=%g km.', link_length, segment_length); end nSegments = round(nSegments); zdw = 1310; randomize_D = true; if nSegments > 0 Dvec = getDispersionVector(nSegments, d_local, zdw, randomize_D, s.random_key); else Dvec = []; end %% Run WITHOUT GPU fprintf('\n========== Running WITHOUT GPU (CPU) ==========\n'); Opt_sig_cpu = Opt_sig_input; tic; for seg = 1:nSegments fprintf('CPU Segment %d/%d \n',seg, nSegments); Opt_sig_cpu = DP_Fiber("L",segment_length,"D",Dvec(seg),"Dpmd",s.pmd,"Ds",0.07, ... "beat_len",10,"corr_len",100,"dz",1,"manakov",0, ... "gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01, ... "SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1,"useGPU",false).process(Opt_sig_cpu); end time_cpu = toc; fprintf('CPU Time: %.3f seconds\n', time_cpu); %% Run WITH GPU (Double Precision) fprintf('\n========== Running WITH GPU (Double Precision) ==========\n'); Opt_sig_gpu_double = Opt_sig_input; tic; for seg = 1:nSegments fprintf('GPU-Double Segment %d/%d \n',seg, nSegments); Opt_sig_gpu_double = DP_Fiber("L",segment_length,"D",Dvec(seg),"Dpmd",s.pmd,"Ds",0.07, ... "beat_len",10,"corr_len",100,"dz",1,"manakov",0, ... "gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01, ... "SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1,"useGPU",true,"useSingle",false).process(Opt_sig_gpu_double); end time_gpu_double = toc; fprintf('GPU Double Time: %.3f seconds\n', time_gpu_double); %% Run WITH GPU (Single Precision) fprintf('\n========== Running WITH GPU (Single Precision) ==========\n'); Opt_sig_gpu_single = Opt_sig_input; tic; for seg = 1:nSegments fprintf('GPU-Single Segment %d/%d \n',seg, nSegments); Opt_sig_gpu_single = DP_Fiber("L",segment_length,"D",Dvec(seg),"Dpmd",s.pmd,"Ds",0.07, ... "beat_len",10,"corr_len",100,"dz",1,"manakov",0, ... "gamma",s.gamma,"lambda",zdw,"n_waveplates",10,"SS_dphimax",0.01, ... "SS_dzmax",50,"SS_dzmin",10,"X_alpha",0.3,"X_beta",0,"rng",1,"useGPU",true,"useSingle",true).process(Opt_sig_gpu_single); end time_gpu_single = toc; fprintf('GPU Single Time: %.3f seconds\n', time_gpu_single); %% Compare Results fprintf('\n========== Numerical Comparison ==========\n'); sig_cpu = Opt_sig_cpu.signal; sig_gpu_double = Opt_sig_gpu_double.signal; sig_gpu_single = Opt_sig_gpu_single.signal; % Check dimensions fprintf('CPU signal size: [%d x %d]\n', size(sig_cpu,1), size(sig_cpu,2)); fprintf('GPU Double signal size: [%d x %d]\n', size(sig_gpu_double,1), size(sig_gpu_double,2)); fprintf('GPU Single signal size: [%d x %d]\n', size(sig_gpu_single,1), size(sig_gpu_single,2)); % CPU vs GPU Double fprintf('\n--- CPU vs GPU Double ---\n'); diff_cpu_double = abs(sig_cpu - sig_gpu_double); max_diff_cpu_double = max(diff_cpu_double(:)); mean_diff_cpu_double = mean(diff_cpu_double(:)); rel_diff_cpu_double = max_diff_cpu_double / max(abs(sig_cpu(:))); fprintf('Max absolute difference: %.6e\n', max_diff_cpu_double); fprintf('Mean absolute difference: %.6e\n', mean_diff_cpu_double); fprintf('Max relative difference: %.6e\n', rel_diff_cpu_double); % CPU vs GPU Single fprintf('\n--- CPU vs GPU Single ---\n'); diff_cpu_single = abs(sig_cpu - sig_gpu_single); max_diff_cpu_single = max(diff_cpu_single(:)); mean_diff_cpu_single = mean(diff_cpu_single(:)); rel_diff_cpu_single = max_diff_cpu_single / max(abs(sig_cpu(:))); fprintf('Max absolute difference: %.6e\n', max_diff_cpu_single); fprintf('Mean absolute difference: %.6e\n', mean_diff_cpu_single); fprintf('Max relative difference: %.6e\n', rel_diff_cpu_single); % GPU Double vs GPU Single fprintf('\n--- GPU Double vs GPU Single ---\n'); diff_double_single = abs(sig_gpu_double - sig_gpu_single); max_diff_double_single = max(diff_double_single(:)); mean_diff_double_single = mean(diff_double_single(:)); rel_diff_double_single = max_diff_double_single / max(abs(sig_gpu_double(:))); fprintf('Max absolute difference: %.6e\n', max_diff_double_single); fprintf('Mean absolute difference: %.6e\n', mean_diff_double_single); fprintf('Max relative difference: %.6e\n', rel_diff_double_single); % Check tolerances fprintf('\n--- Tolerance Check ---\n'); tol_double = 1e-10; tol_single = 1e-5; % Single precision has ~7 significant digits if max_diff_cpu_double < tol_double fprintf('✓ CPU vs GPU Double: EQUIVALENT (diff < %.0e)\n', tol_double); else fprintf('✗ CPU vs GPU Double: DIFFER beyond tolerance (%.0e)\n', tol_double); end if max_diff_cpu_single < tol_single fprintf('✓ CPU vs GPU Single: ACCEPTABLE (diff < %.0e)\n', tol_single); else fprintf('⚠ CPU vs GPU Single: Precision loss detected (diff = %.2e, tol = %.0e)\n', max_diff_cpu_single, tol_single); end % Performance comparison fprintf('\n========== Performance Summary ==========\n'); fprintf('CPU Time: %.3f s\n', time_cpu); fprintf('GPU Double Time: %.3f s\n', time_gpu_double); fprintf('GPU Single Time: %.3f s\n', time_gpu_single); fprintf('\n'); fprintf('Speedup (GPU Double vs CPU): %.2fx\n', time_cpu/time_gpu_double); fprintf('Speedup (GPU Single vs CPU): %.2fx\n', time_cpu/time_gpu_single); fprintf('Speedup (GPU Single vs GPU Double): %.2fx\n', time_gpu_double/time_gpu_single); %% ========== BER Comparison ========== % Process each fiber output through simplified receiver to check if % single-precision affects actual BER performance fprintf('\n========== BER Comparison ==========\n'); fprintf('Processing signals through receiver chain...\n'); % Receiver parameters rop = -7; % Received optical power [dBm] len_tr = 4096; % Training length mu_dc = 0.005; mu_ffe = [0.0001 0.0008 0.001]; mu_dfe = 0.0004; % Helper function to process through receiver and get BER function ber = process_receiver(Opt_sig_fib, l, Symbols, Tx_bits, ... fdac, kover, upsample_pow, fsym, fadc, rop, s, len_tr, mu_dc, mu_ffe, mu_dfe, duob_mode) % Demux single channel Opt_sig_demux = Optical_Demultiplex("attenuation",0,"B",200e9,"filtype",1, ... "fs_out",fdac*kover,"fs_in",fdac*kover*upsample_pow,"lambda_center",1310).process(Opt_sig_fib); % ROP amplifier Opt_sig_rx = Amplifier("amp_mode","ideal_no_noise","gain_mode","output_power", ... "amplification_db",rop).process(Opt_sig_demux{l}); % Photodiode PD_sig = Photodiode("fsimu",fdac*kover,"dark_current",2e-08,"responsivity",1,"temperature",20, ... "nep",1.8e-11,"randomkey",s.random_key+l).process(Opt_sig_rx); % Low-pass filter rx_bwl = 100e9; PD_sig = Filter('filtdegree',4,"f_cutoff",rx_bwl,"fs",fdac*kover, ... "filterType",filtertypes.butterworth,"active",true).process(PD_sig); % Scope Lp_scpe = Filter('filtdegree',4,"f_cutoff",80e9,"fs",fadc,"filterType",filtertypes.butterworth,"active",true); Scpe_sig = Scope("fsimu",fdac*kover,"fadc",fadc, ... "delay",0,"fixed_delay",0,"filtertype",filtertypes.butterworth, ... "samplingdelay",0,"rand_samplingdelay",0,"freq_offset",0,"samp_jitter",0, ... "adcresolution",8,"quantbuffer",0.1,'block_dc',1,'lpf_active',0,'H_lpf',Lp_scpe).process(PD_sig); % Resample to 2 sps Scpe_sig_2sps = Scpe_sig.resample("fs_out",2*fsym); % Time sync [~, Scpe_cell, ~, ~] = Scpe_sig_2sps.tsynch("reference", Symbols{l}, "fs_ref", fsym, "debug_plots", 0); Rx_sig = Scpe_cell{1}; Rx_sig = Rx_sig.normalize("mode","rms"); % FFE Equalizer ffe_order = [50, 0, 0]; eq_ffe = EQ("Ne",ffe_order,"Nb",[0,0,0],"training_length",len_tr,"training_loops",5,"dd_loops",5, ... "K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0); ffe_results = ffe(eq_ffe,s.M,Rx_sig,Symbols{l},Tx_bits{l}, ... "precode_mode",duob_mode, ... 'showAnalysis',0, ... "postFFE",[], ... "eth_style_symbol_mapping",0); ber = ffe_results.metrics.BER; end % Process each mode for channel 1 l = 4; % Use first channel for comparison fprintf('Processing CPU result...\n'); ber_cpu = process_receiver(Opt_sig_cpu, l, Symbols, Tx_bits, ... fdac, kover, upsample_pow, fsym, fadc, rop, s, len_tr, mu_dc, mu_ffe, mu_dfe, duob_mode); fprintf('Processing GPU Double result...\n'); ber_gpu_double = process_receiver(Opt_sig_gpu_double, l, Symbols, Tx_bits, ... fdac, kover, upsample_pow, fsym, fadc, rop, s, len_tr, mu_dc, mu_ffe, mu_dfe, duob_mode); fprintf('Processing GPU Single result...\n'); ber_gpu_single = process_receiver(Opt_sig_gpu_single, l, Symbols, Tx_bits, ... fdac, kover, upsample_pow, fsym, fadc, rop, s, len_tr, mu_dc, mu_ffe, mu_dfe, duob_mode); % Display BER results fprintf('\n========== BER Results (Channel %d, ROP = %d dBm) ==========\n', l, rop); fprintf('CPU: BER = %.4e\n', ber_cpu); fprintf('GPU Double: BER = %.4e\n', ber_gpu_double); fprintf('GPU Single: BER = %.4e\n', ber_gpu_single); fprintf('\n--- BER Comparison ---\n'); if ber_cpu == 0 && ber_gpu_double == 0 && ber_gpu_single == 0 fprintf('✓ All BERs are zero (no errors detected)\n'); else ber_diff_double = abs(ber_cpu - ber_gpu_double); ber_diff_single = abs(ber_cpu - ber_gpu_single); fprintf('|BER_cpu - BER_gpu_double| = %.4e\n', ber_diff_double); fprintf('|BER_cpu - BER_gpu_single| = %.4e\n', ber_diff_single); if ber_diff_double < 1e-6 && ber_diff_single < 1e-6 fprintf('✓ BER differences are negligible\n'); elseif ber_diff_single > ber_diff_double * 10 fprintf('⚠ Single precision shows measurable BER impact\n'); else fprintf('✓ BER differences within acceptable range\n'); end end fprintf('\n========== Test Complete ==========\n');