mirror of
https://github.com/gnss-sdr/gnss-sdr
synced 2025-03-28 14:27:03 +00:00
Updated CUDA kernels and several GPU tracking optimizations.
Bug fix in GPS_L1_CA_DLL_PLL binary dump
This commit is contained in:
Javier Arribas
parent
26cf90cdd4
commit
1aa84cd1c4
@ -165,7 +165,7 @@ Resampler.sample_freq_out=4000000
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;######### CHANNELS GLOBAL CONFIG ############
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;#count: Number of available GPS satellite channels.
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Channels_GPS.count=8
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Channels_GPS.count=1
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;#count: Number of available Galileo satellite channels.
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Channels_Galileo.count=0
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;#in_acquisition: Number of channels simultaneously acquiring for the whole receiver
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@ -229,16 +229,16 @@ Tracking_GPS.item_type=gr_complex
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Tracking_GPS.if=0
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;#dump: Enable or disable the Tracking internal binary data file logging [true] or [false]
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Tracking_GPS.dump=false
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Tracking_GPS.dump=true
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;#dump_filename: Log path and filename. Notice that the tracking channel will add "x.dat" where x is the channel number.
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Tracking_GPS.dump_filename=../data/epl_tracking_ch_
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;#pll_bw_hz: PLL loop filter bandwidth [Hz]
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Tracking_GPS.pll_bw_hz=45.0;
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Tracking_GPS.pll_bw_hz=55.0;
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;#dll_bw_hz: DLL loop filter bandwidth [Hz]
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Tracking_GPS.dll_bw_hz=2.0;
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Tracking_GPS.dll_bw_hz=1.5
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;#fll_bw_hz: FLL loop filter bandwidth [Hz]
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Tracking_GPS.fll_bw_hz=10.0;
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@ -29,13 +29,13 @@ GNSS-SDR.SUPL_CI=0x31b0
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SignalSource.implementation=Flexiband_Signal_Source
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SignalSource.flag_read_file=true
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SignalSource.signal_file=/datalogger/captures/eclipse/eclipse_IIIa_2.bin
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SignalSource.signal_file=/datalogger/L125_III1b_210s.usb
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;#item_type: Type and resolution for each of the signal samples. Use only gr_complex in this version.
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SignalSource.item_type=gr_complex
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;# FPGA firmware file
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SignalSource.firmware_file=flexiband_III-1a.bit
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SignalSource.firmware_file=flexiband_III-1b.bit
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;#RF_channels: Number of RF channels present in the frontend device, must agree the FPGA firmware file
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SignalSource.RF_channels=1
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@ -28,9 +28,9 @@ GNSS-SDR.SUPL_CI=0x31b0
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;#implementation: Use [File_Signal_Source] or [UHD_Signal_Source] or [GN3S_Signal_Source] (experimental)
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SignalSource.implementation=Flexiband_Signal_Source
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SignalSource.flag_read_file=false
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#SignalSource.signal_file=/datalogger/signals/Fraunhofer/L125_III1b_210s.usb
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SignalSource.signal_file=/datalogger/captures/flexiband_III_1b_cap1.usb
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SignalSource.flag_read_file=true
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SignalSource.signal_file=/datalogger/L125_III1b_210s.usb
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#SignalSource.signal_file=/datalogger/captures/flexiband_III_1b_cap1.usb
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;#item_type: Type and resolution for each of the signal samples. Use only gr_complex in this version.
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SignalSource.item_type=gr_complex
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@ -136,8 +136,8 @@ InputFilter0.grid_density=16
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InputFilter0.sampling_frequency=20000000
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;# IF deviation due to front-end LO inaccuracies [HZ]
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;# WARNING: Fraunhofer front-end hardwareconfigurations can difer. Signals available on http://www.iis.fraunhofer.de/de/ff/lok/leist/test/flexiband.html are centered on 0 Hz, ALL BANDS.
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InputFilter0.IF=-205000
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;#InputFilter0.IF=0
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;#InputFilter0.IF=-205000
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InputFilter0.IF=0
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;# Decimation factor after the frequency tranaslating block
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InputFilter0.decimation_factor=8
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@ -230,8 +230,8 @@ InputFilter1.grid_density=16
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InputFilter1.sampling_frequency=20000000
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;# IF deviation due to front-end LO inaccuracies [HZ]
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;# WARNING: Fraunhofer front-end hardwareconfigurations can difer. Signals available on http://www.iis.fraunhofer.de/de/ff/lok/leist/test/flexiband.html are centered on 0 Hz, ALL BANDS.
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InputFilter1.IF=100000
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;#InputFilter1.IF=0
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;#InputFilter1.IF=100000
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InputFilter1.IF=0
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;# Decimation factor after the frequency tranaslating block
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InputFilter1.decimation_factor=8
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@ -272,7 +272,7 @@ Resampler2.implementation=Pass_Through
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;#count: Number of available GPS satellite channels.
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Channels_1C.count=8
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Channels_1B.count=1
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Channels_2S.count=8
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Channels_2S.count=1
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;#count: Number of available Galileo satellite channels.
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;Channels_Galileo.count=0
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;#in_acquisition: Number of channels simultaneously acquiring for the whole receiver
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@ -378,13 +378,13 @@ Acquisition_1C.max_dwells=1
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;#implementation: Selected tracking algorithm: [GPS_L1_CA_DLL_PLL_Tracking] or [GPS_L1_CA_DLL_FLL_PLL_Tracking]
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Tracking_1C.implementation=GPS_L1_CA_DLL_PLL_Tracking
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Tracking_1C.implementation=GPS_L1_CA_DLL_PLL_Tracking_GPU
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Tracking_1C.item_type=gr_complex
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Tracking_1C.if=0
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Tracking_1C.dump=true
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Tracking_1C.dump_filename=./tracking_ch_
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Tracking_1C.dump=false
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Tracking_1C.dump_filename=../data/epl_tracking_ch_
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Tracking_1C.pll_bw_hz=40.0;
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Tracking_1C.dll_bw_hz=3.0;
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Tracking_1C.dll_bw_hz=1.5;
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Tracking_1C.fll_bw_hz=10.0;
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Tracking_1C.order=3;
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Tracking_1C.early_late_space_chips=0.5;
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@ -405,7 +405,7 @@ Acquisition_2S.max_dwells=1
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Tracking_2S.implementation=GPS_L2_M_DLL_PLL_Tracking
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Tracking_2S.item_type=gr_complex
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Tracking_2S.if=0
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Tracking_2S.dump=true
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Tracking_2S.dump=false
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Tracking_2S.dump_filename=./tracking_ch_
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Tracking_2S.pll_bw_hz=1.5;
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Tracking_2S.dll_bw_hz=0.3;
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@ -447,7 +447,7 @@ Tracking_1B.item_type=gr_complex
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Tracking_1B.if=0
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;#dump: Enable or disable the Tracking internal binary data file logging [true] or [false]
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Tracking_1B.dump=true
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Tracking_1B.dump=false
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;#dump_filename: Log path and filename. Notice that the tracking channel will add "x.dat" where x is the channel number.
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Tracking_1B.dump_filename=./veml_tracking_ch_
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@ -497,7 +497,7 @@ TelemetryDecoder_1B.decimation_factor=5;
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Observables.implementation=Mixed_Observables
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;#dump: Enable or disable the Observables internal binary data file logging [true] or [false]
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Observables.dump=true
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Observables.dump=false
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;#dump_filename: Log path and filename.
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Observables.dump_filename=./observables.dat
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@ -135,7 +135,8 @@ InputFilter0.grid_density=16
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; i.e. using front-end-cal as reported here:http://www.cttc.es/publication/turning-a-television-into-a-gnss-receiver/
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InputFilter0.sampling_frequency=20000000
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;# IF deviation due to front-end LO inaccuracies [HZ]
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InputFilter0.IF=-205000
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;#InputFilter0.IF=-205000
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InputFilter0.IF=0
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;# Decimation factor after the frequency tranaslating block
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InputFilter0.decimation_factor=4
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@ -58,7 +58,7 @@ if(ENABLE_FLEXIBAND)
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if(OS_IS_MACOSX)
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set(MACOSX_ARGS "-DCMAKE_CXX_COMPILER=/usr/bin/clang++")
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endif(OS_IS_MACOSX)
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find_package(teleorbit REQUIRED)
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find_package(Teleorbit REQUIRED)
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if(NOT TELEORBIT_FOUND)
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message(FATAL_ERROR "Teleorbit Flexiband GNURadio driver required to build gnss-sdr with the optional FLEXIBAND adapter")
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endif(NOT TELEORBIT_FOUND)
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@ -18,6 +18,7 @@
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if(ENABLE_CUDA)
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FIND_PACKAGE(CUDA REQUIRED)
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set(OPT_TRACKING_ADAPTERS ${OPT_TRACKING_ADAPTERS} gps_l1_ca_dll_pll_tracking_gpu.cc)
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endif(ENABLE_CUDA)
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set(TRACKING_ADAPTER_SOURCES
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@ -30,7 +31,7 @@ set(TRACKING_ADAPTER_SOURCES
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gps_l1_ca_tcp_connector_tracking.cc
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galileo_e5a_dll_pll_tracking.cc
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gps_l2_m_dll_pll_tracking.cc
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gps_l1_ca_dll_pll_tracking_gpu.cc
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${OPT_TRACKING_ADAPTERS}
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)
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include_directories(
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@ -19,6 +19,7 @@
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if(ENABLE_CUDA)
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FIND_PACKAGE(CUDA REQUIRED)
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set(OPT_TRACKING_BLOCKS ${OPT_TRACKING_BLOCKS} gps_l1_ca_dll_pll_tracking_gpu_cc.cc)
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endif(ENABLE_CUDA)
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set(TRACKING_GR_BLOCKS_SOURCES
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@ -31,7 +32,7 @@ set(TRACKING_GR_BLOCKS_SOURCES
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gps_l1_ca_tcp_connector_tracking_cc.cc
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galileo_e5a_dll_pll_tracking_cc.cc
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gps_l2_m_dll_pll_tracking_cc.cc
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gps_l1_ca_dll_pll_tracking_gpu_cc.cc
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${OPT_TRACKING_BLOCKS}
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)
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include_directories(
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@ -594,7 +594,8 @@ int Gps_L1_Ca_Dll_Pll_Tracking_cc::general_work (int noutput_items, gr_vector_in
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// carrier and code frequency
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d_dump_file.write(reinterpret_cast<char*>(&d_carrier_doppler_hz), sizeof(float));
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d_dump_file.write(reinterpret_cast<char*>(&d_code_freq_chips), sizeof(float));
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tmp_float=d_code_freq_chips;
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d_dump_file.write(reinterpret_cast<char*>(&tmp_float), sizeof(float));
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//PLL commands
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d_dump_file.write(reinterpret_cast<char*>(&carr_error_hz), sizeof(float));
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@ -81,7 +81,6 @@ gps_l1_ca_dll_pll_make_tracking_gpu_cc(
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}
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void Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::forecast (int noutput_items,
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gr_vector_int &ninput_items_required)
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{
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@ -120,14 +119,19 @@ Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc(
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// Initialization of local code replica
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// Get space for a vector with the C/A code replica sampled 1x/chip
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d_ca_code = static_cast<gr_complex*>(volk_malloc((GPS_L1_CA_CODE_LENGTH_CHIPS + 2) * sizeof(gr_complex), volk_get_alignment()));
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//d_ca_code = static_cast<gr_complex*>(volk_malloc((GPS_L1_CA_CODE_LENGTH_CHIPS + 2) * sizeof(gr_complex), volk_get_alignment()));
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d_ca_code = static_cast<gr_complex*>(volk_malloc((GPS_L1_CA_CODE_LENGTH_CHIPS) * sizeof(gr_complex), volk_get_alignment()));
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multicorrelator_gpu = new cuda_multicorrelator();
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int N_CORRELATORS=3;
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multicorrelator_gpu->init_cuda(0, NULL, 2 * d_vector_length , 2 * d_vector_length , N_CORRELATORS);
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//local code resampler on CPU (old)
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//multicorrelator_gpu->init_cuda(0, NULL, 2 * d_vector_length , 2 * d_vector_length , N_CORRELATORS);
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//local code resampler on GPU (new)
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multicorrelator_gpu->init_cuda_integrated_resampler(0, NULL, 2 * d_vector_length , GPS_L1_CA_CODE_LENGTH_CHIPS , N_CORRELATORS);
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// Get space for the resampled early / prompt / late local replicas
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checkCudaErrors(cudaHostAlloc((void**)&d_local_code_shift_samples, N_CORRELATORS * sizeof(int), cudaHostAllocMapped ));
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checkCudaErrors(cudaHostAlloc((void**)&d_local_code_shift_chips, N_CORRELATORS * sizeof(float), cudaHostAllocMapped ));
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//allocate host memory
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@ -138,7 +142,7 @@ Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc(
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//checkCudaErrors(cudaHostAlloc((void**)&d_local_codes_gpu, (V_LEN * sizeof(gr_complex))*N_CORRELATORS, cudaHostAllocWriteCombined ));
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//new integrated shifts
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checkCudaErrors(cudaHostAlloc((void**)&d_local_codes_gpu, (2 * d_vector_length * sizeof(gr_complex)), cudaHostAllocWriteCombined ));
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//checkCudaErrors(cudaHostAlloc((void**)&d_local_codes_gpu, (2 * d_vector_length * sizeof(gr_complex)), cudaHostAllocWriteCombined ));
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// correlator outputs (scalar)
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checkCudaErrors(cudaHostAlloc((void**)&d_corr_outs_gpu ,sizeof(gr_complex)*N_CORRELATORS, cudaHostAllocWriteCombined ));
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@ -242,9 +246,13 @@ void Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::start_tracking()
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d_code_loop_filter.initialize(); // initialize the code filter
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// generate local reference ALWAYS starting at chip 1 (1 sample per chip)
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gps_l1_ca_code_gen_complex(&d_ca_code[1], d_acquisition_gnss_synchro->PRN, 0);
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d_ca_code[0] = d_ca_code[static_cast<int>(GPS_L1_CA_CODE_LENGTH_CHIPS)];
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d_ca_code[static_cast<int>(GPS_L1_CA_CODE_LENGTH_CHIPS) + 1] = d_ca_code[1];
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gps_l1_ca_code_gen_complex(d_ca_code, d_acquisition_gnss_synchro->PRN, 0);
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d_local_code_shift_chips[0]=-d_early_late_spc_chips;
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d_local_code_shift_chips[1]=0.0;
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d_local_code_shift_chips[2]=d_early_late_spc_chips;
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multicorrelator_gpu->set_local_code_and_taps(GPS_L1_CA_CODE_LENGTH_CHIPS,d_ca_code, d_local_code_shift_chips,3);
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d_carrier_lock_fail_counter = 0;
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d_rem_code_phase_samples = 0;
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@ -272,40 +280,6 @@ void Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::start_tracking()
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}
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void Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::update_local_code()
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{
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double tcode_chips;
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double rem_code_phase_chips;
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int associated_chip_index;
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int code_length_chips = static_cast<int>(GPS_L1_CA_CODE_LENGTH_CHIPS);
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double code_phase_step_chips;
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int epl_loop_length_samples;
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// unified loop for E, P, L code vectors
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code_phase_step_chips = static_cast<double>(d_code_freq_chips) / static_cast<double>(d_fs_in);
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rem_code_phase_chips = d_rem_code_phase_samples * (d_code_freq_chips / d_fs_in);
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tcode_chips = -rem_code_phase_chips;
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// Alternative EPL code generation (40% of speed improvement!)
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d_local_code_shift_samples[0]=0;
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d_local_code_shift_samples[1]=round(d_early_late_spc_chips / code_phase_step_chips);
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d_local_code_shift_samples[2]=round((2*d_early_late_spc_chips) / code_phase_step_chips);
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epl_loop_length_samples = d_current_prn_length_samples + d_local_code_shift_samples[2]; //maximum length
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for (int i = 0; i < epl_loop_length_samples; i++)
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{
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associated_chip_index = 1 + round(fmod(tcode_chips - d_early_late_spc_chips, code_length_chips));
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d_local_codes_gpu[i] = d_ca_code[associated_chip_index];
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tcode_chips = tcode_chips + code_phase_step_chips;
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}
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}
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Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::~Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc()
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{
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d_dump_file.close();
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@ -313,7 +287,7 @@ Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::~Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc()
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cudaFreeHost(in_gpu);
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cudaFreeHost(d_carr_sign_gpu);
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cudaFreeHost(d_corr_outs_gpu);
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cudaFreeHost(d_local_codes_gpu);
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cudaFreeHost(d_local_code_shift_chips);
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multicorrelator_gpu->free_cuda();
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delete(multicorrelator_gpu);
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@ -329,10 +303,10 @@ int Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::general_work (int noutput_items, gr_vecto
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gr_vector_const_void_star &input_items, gr_vector_void_star &output_items)
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{
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// process vars
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float carr_error_hz;
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float carr_error_filt_hz;
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float code_error_chips;
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float code_error_filt_chips;
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float carr_error_hz=0.0;
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float carr_error_filt_hz=0.0;
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float code_error_chips=0.0;
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float code_error_filt_chips=0.0;
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// Block input data and block output stream pointers
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const gr_complex* in = (gr_complex*) input_items[0];
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@ -341,23 +315,17 @@ int Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::general_work (int noutput_items, gr_vecto
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// GNSS_SYNCHRO OBJECT to interchange data between tracking->telemetry_decoder
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Gnss_Synchro current_synchro_data = Gnss_Synchro();
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if (d_enable_tracking == true)
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{
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// Receiver signal alignment
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if (d_pull_in == true)
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{
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int samples_offset;
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float acq_trk_shif_correction_samples;
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int acq_to_trk_delay_samples;
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acq_to_trk_delay_samples = d_sample_counter - d_acq_sample_stamp;
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acq_trk_shif_correction_samples = d_current_prn_length_samples - fmod(static_cast<float>(acq_to_trk_delay_samples), static_cast<float>(d_current_prn_length_samples));
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samples_offset = round(d_acq_code_phase_samples + acq_trk_shif_correction_samples);
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// /todo: Check if the sample counter sent to the next block as a time reference should be incremented AFTER sended or BEFORE
|
||||
//d_sample_counter_seconds = d_sample_counter_seconds + (((double)samples_offset) / static_cast<double>(d_fs_in));
|
||||
samples_offset = round(d_acq_code_phase_samples)+d_current_prn_length_samples - acq_to_trk_delay_samples%d_current_prn_length_samples;
|
||||
d_sample_counter = d_sample_counter + samples_offset; //count for the processed samples
|
||||
d_pull_in = false;
|
||||
//std::cout<<" samples_offset="<<samples_offset<<"\r\n";
|
||||
// Fill the acquisition data
|
||||
current_synchro_data = *d_acquisition_gnss_synchro;
|
||||
*out[0] = current_synchro_data;
|
||||
@ -368,46 +336,24 @@ int Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::general_work (int noutput_items, gr_vecto
|
||||
// Fill the acquisition data
|
||||
current_synchro_data = *d_acquisition_gnss_synchro;
|
||||
|
||||
// Generate local code and carrier replicas (using \hat{f}_d(k-1))
|
||||
update_local_code();
|
||||
|
||||
// UPDATE NCO COMMAND
|
||||
float phase_step_rad = static_cast<float>(GPS_TWO_PI) * d_carrier_doppler_hz / static_cast<float>(d_fs_in);
|
||||
//std::cout<<"d_current_prn_length_samples="<<d_current_prn_length_samples<<std::endl;
|
||||
// perform carrier wipe-off and compute Early, Prompt and Late correlation
|
||||
cudaProfilerStart();
|
||||
multicorrelator_gpu->Carrier_wipeoff_multicorrelator_cuda(
|
||||
|
||||
//code resampler on GPU (new)
|
||||
float code_phase_step_chips = static_cast<float>(d_code_freq_chips) / static_cast<float>(d_fs_in);
|
||||
float rem_code_phase_chips = d_rem_code_phase_samples * (d_code_freq_chips / d_fs_in);
|
||||
|
||||
cudaProfilerStart();
|
||||
multicorrelator_gpu->Carrier_wipeoff_multicorrelator_resampler_cuda(
|
||||
d_corr_outs_gpu,
|
||||
in,
|
||||
d_local_codes_gpu,
|
||||
d_rem_carr_phase_rad,
|
||||
phase_step_rad,
|
||||
d_local_code_shift_samples,
|
||||
code_phase_step_chips,
|
||||
rem_code_phase_chips,
|
||||
d_current_prn_length_samples,
|
||||
3);
|
||||
cudaProfilerStop();
|
||||
//std::cout<<"d_Prompt="<<*d_Prompt<<"d_Early="<<*d_Early<<"d_Late="<<*d_Late<<std::endl;
|
||||
// check for samples consistency (this should be done before in the receiver / here only if the source is a file)
|
||||
if (std::isnan((*d_Prompt).real()) == true or std::isnan((*d_Prompt).imag()) == true ) // or std::isinf(in[i].real())==true or std::isinf(in[i].imag())==true)
|
||||
{
|
||||
const int samples_available = ninput_items[0];
|
||||
d_sample_counter = d_sample_counter + samples_available;
|
||||
LOG(WARNING) << "Detected NaN samples at sample number " << d_sample_counter;
|
||||
consume_each(samples_available);
|
||||
|
||||
// make an output to not stop the rest of the processing blocks
|
||||
current_synchro_data.Prompt_I = 0.0;
|
||||
current_synchro_data.Prompt_Q = 0.0;
|
||||
current_synchro_data.Tracking_timestamp_secs = static_cast<double>(d_sample_counter) / static_cast<double>(d_fs_in);
|
||||
current_synchro_data.Carrier_phase_rads = 0.0;
|
||||
current_synchro_data.Code_phase_secs = 0.0;
|
||||
current_synchro_data.CN0_dB_hz = 0.0;
|
||||
current_synchro_data.Flag_valid_tracking = false;
|
||||
current_synchro_data.Flag_valid_pseudorange = false;
|
||||
|
||||
*out[0] = current_synchro_data;
|
||||
return 1;
|
||||
}
|
||||
|
||||
// ################## PLL ##########################################################
|
||||
// PLL discriminator
|
||||
@ -444,8 +390,7 @@ int Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::general_work (int noutput_items, gr_vecto
|
||||
T_chip_seconds = 1 / static_cast<double>(d_code_freq_chips);
|
||||
T_prn_seconds = T_chip_seconds * GPS_L1_CA_CODE_LENGTH_CHIPS;
|
||||
T_prn_samples = T_prn_seconds * static_cast<double>(d_fs_in);
|
||||
K_blk_samples = T_prn_samples + d_rem_code_phase_samples + code_error_filt_secs * static_cast<double>(d_fs_in);
|
||||
d_current_prn_length_samples = round(K_blk_samples); //round to a discrete samples
|
||||
K_blk_samples = T_prn_samples + d_rem_code_phase_samples + static_cast<double>(code_error_filt_secs) * static_cast<double>(d_fs_in);
|
||||
//d_rem_code_phase_samples = K_blk_samples - d_current_prn_length_samples; //rounding error < 1 sample
|
||||
|
||||
// ####### CN0 ESTIMATION AND LOCK DETECTORS ######
|
||||
@ -591,7 +536,8 @@ int Gps_L1_Ca_Dll_Pll_Tracking_GPU_cc::general_work (int noutput_items, gr_vecto
|
||||
|
||||
// carrier and code frequency
|
||||
d_dump_file.write(reinterpret_cast<char*>(&d_carrier_doppler_hz), sizeof(float));
|
||||
d_dump_file.write(reinterpret_cast<char*>(&d_code_freq_chips), sizeof(float));
|
||||
tmp_float=d_code_freq_chips;
|
||||
d_dump_file.write(reinterpret_cast<char*>(&tmp_float), sizeof(float));
|
||||
|
||||
//PLL commands
|
||||
d_dump_file.write(reinterpret_cast<char*>(&carr_error_hz), sizeof(float));
|
||||
|
||||
@ -130,7 +130,7 @@ private:
|
||||
gr_complex* in_gpu;
|
||||
gr_complex* d_carr_sign_gpu;
|
||||
gr_complex* d_local_codes_gpu;
|
||||
int* d_local_code_shift_samples;
|
||||
float* d_local_code_shift_chips;
|
||||
gr_complex* d_corr_outs_gpu;
|
||||
cuda_multicorrelator *multicorrelator_gpu;
|
||||
|
||||
|
||||
@ -33,7 +33,6 @@ if(ENABLE_CUDA)
|
||||
|
||||
SET(LIB_TYPE STATIC) #set the lib type
|
||||
CUDA_ADD_LIBRARY(CUDA_CORRELATOR_LIB ${LIB_TYPE} cuda_multicorrelator.h cuda_multicorrelator.cu)
|
||||
|
||||
endif(ENABLE_CUDA)
|
||||
|
||||
|
||||
|
||||
@ -53,7 +53,83 @@
|
||||
#include <helper_cuda.h>
|
||||
#include <helper_functions.h>
|
||||
|
||||
#define ACCUM_N 1024
|
||||
#define ACCUM_N 256
|
||||
|
||||
|
||||
__global__ void scalarProdGPUCPXxN_shifts_chips(
|
||||
GPU_Complex *d_corr_out,
|
||||
GPU_Complex *d_sig_in,
|
||||
GPU_Complex *d_local_code_in,
|
||||
float *d_shifts_chips,
|
||||
float code_length_chips,
|
||||
float code_phase_step_chips,
|
||||
float rem_code_phase_chips,
|
||||
int vectorN,
|
||||
int elementN
|
||||
)
|
||||
{
|
||||
//Accumulators cache
|
||||
__shared__ GPU_Complex accumResult[ACCUM_N];
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////
|
||||
// Cycle through every pair of vectors,
|
||||
// taking into account that vector counts can be different
|
||||
// from total number of thread blocks
|
||||
////////////////////////////////////////////////////////////////////////////
|
||||
for (int vec = blockIdx.x; vec < vectorN; vec += gridDim.x)
|
||||
{
|
||||
//int vectorBase = IMUL(elementN, vec);
|
||||
//int vectorEnd = elementN;
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Each accumulator cycles through vectors with
|
||||
// stride equal to number of total number of accumulators ACCUM_N
|
||||
// At this stage ACCUM_N is only preferred be a multiple of warp size
|
||||
// to meet memory coalescing alignment constraints.
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
for (int iAccum = threadIdx.x; iAccum < ACCUM_N; iAccum += blockDim.x)
|
||||
{
|
||||
GPU_Complex sum = GPU_Complex(0,0);
|
||||
|
||||
for (int pos = iAccum; pos < elementN; pos += ACCUM_N)
|
||||
{
|
||||
//sum = sum + d_sig_in[pos-vectorBase] * d_nco_in[pos-vectorBase] * d_local_codes_in[pos];
|
||||
//sum = sum + d_sig_in[pos-vectorBase] * d_local_codes_in[pos];
|
||||
//sum.multiply_acc(d_sig_in[pos],d_local_codes_in[pos+d_shifts_samples[vec]]);
|
||||
|
||||
// 1.resample local code for the current shift
|
||||
float local_code_chip_index= fmod(code_phase_step_chips*(float)pos + d_shifts_chips[vec] - rem_code_phase_chips, code_length_chips);
|
||||
//TODO: Take into account that in multitap correlators, the shifts can be negative!
|
||||
if (local_code_chip_index<0.0) local_code_chip_index+=code_length_chips;
|
||||
|
||||
// 2.correlate
|
||||
sum.multiply_acc(d_sig_in[pos],d_local_code_in[__float2int_rd(local_code_chip_index)]);
|
||||
|
||||
}
|
||||
accumResult[iAccum] = sum;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Perform tree-like reduction of accumulators' results.
|
||||
// ACCUM_N has to be power of two at this stage
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
for (int stride = ACCUM_N / 2; stride > 0; stride >>= 1)
|
||||
{
|
||||
__syncthreads();
|
||||
|
||||
for (int iAccum = threadIdx.x; iAccum < stride; iAccum += blockDim.x)
|
||||
{
|
||||
accumResult[iAccum] += accumResult[stride + iAccum];
|
||||
}
|
||||
}
|
||||
|
||||
if (threadIdx.x == 0)
|
||||
{
|
||||
d_corr_out[vec] = accumResult[0];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
// Calculate scalar products of VectorN vectors of ElementN elements on GPU
|
||||
@ -145,8 +221,9 @@ __global__ void scalarProdGPUCPXxN(
|
||||
////////////////////////////////////////////////////////////////////////////
|
||||
for (int vec = blockIdx.x; vec < vectorN; vec += gridDim.x)
|
||||
{
|
||||
int vectorBase = IMUL(elementN, vec);
|
||||
int vectorEnd = vectorBase + elementN;
|
||||
//int vectorBase = IMUL(elementN, vec);
|
||||
//int vectorEnd = vectorBase + elementN;
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Each accumulator cycles through vectors with
|
||||
@ -158,11 +235,13 @@ __global__ void scalarProdGPUCPXxN(
|
||||
{
|
||||
GPU_Complex sum = GPU_Complex(0,0);
|
||||
|
||||
for (int pos = vectorBase + iAccum; pos < vectorEnd; pos += ACCUM_N)
|
||||
//for (int pos = vectorBase + iAccum; pos < vectorEnd; pos += ACCUM_N)
|
||||
for (int pos = iAccum; pos < elementN; pos += ACCUM_N)
|
||||
{
|
||||
//sum = sum + d_sig_in[pos-vectorBase] * d_nco_in[pos-vectorBase] * d_local_codes_in[pos];
|
||||
//sum = sum + d_sig_in[pos-vectorBase] * d_local_codes_in[pos];
|
||||
sum.multiply_acc(d_sig_in[pos-vectorBase],d_local_codes_in[pos]);
|
||||
//sum.multiply_acc(d_sig_in[pos-vectorBase],d_local_codes_in[pos]);
|
||||
sum.multiply_acc(d_sig_in[pos],d_local_codes_in[pos]);
|
||||
}
|
||||
accumResult[iAccum] = sum;
|
||||
}
|
||||
@ -200,9 +279,9 @@ __global__ void scalarProdGPUCPXxN(
|
||||
*/
|
||||
__global__ void CUDA_32fc_x2_multiply_32fc( GPU_Complex *A, GPU_Complex *B, GPU_Complex *C, int numElements)
|
||||
{
|
||||
int i = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
|
||||
if (i < numElements)
|
||||
for (int i = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
i < numElements;
|
||||
i += blockDim.x * gridDim.x)
|
||||
{
|
||||
C[i] = A[i] * B[i];
|
||||
}
|
||||
@ -232,10 +311,11 @@ CUDA_32fc_Doppler_wipeoff( GPU_Complex *sig_out, GPU_Complex *sig_in, float rem
|
||||
|
||||
// CUDA version of floating point NCO and vector dot product integrated
|
||||
|
||||
int i = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
float sin;
|
||||
float cos;
|
||||
if (i < numElements)
|
||||
for (int i = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
i < numElements;
|
||||
i += blockDim.x * gridDim.x)
|
||||
{
|
||||
__sincosf(rem_carrier_phase_in_rad + i*phase_step_rad, &sin, &cos);
|
||||
sig_out[i] = sig_in[i] * GPU_Complex(cos,-sin);
|
||||
@ -252,11 +332,11 @@ CUDA_32fc_Doppler_wipeoff( GPU_Complex *sig_out, GPU_Complex *sig_in, float rem
|
||||
__global__ void
|
||||
CUDA_32fc_x2_add_32fc( GPU_Complex *A, GPU_Complex *B, GPU_Complex *C, int numElements)
|
||||
{
|
||||
int i = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
|
||||
if (i < numElements)
|
||||
for (int i = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
i < numElements;
|
||||
i += blockDim.x * gridDim.x)
|
||||
{
|
||||
C[i] = A[i] * B[i];
|
||||
C[i] = A[i] + B[i];
|
||||
}
|
||||
}
|
||||
|
||||
@ -264,23 +344,53 @@ CUDA_32fc_x2_add_32fc( GPU_Complex *A, GPU_Complex *B, GPU_Complex *C, int
|
||||
bool cuda_multicorrelator::init_cuda(const int argc, const char **argv, int signal_length_samples, int local_codes_length_samples, int n_correlators)
|
||||
{
|
||||
// use command-line specified CUDA device, otherwise use device with highest Gflops/s
|
||||
findCudaDevice(argc, (const char **)argv);
|
||||
|
||||
cudaDeviceProp prop;
|
||||
int whichDevice;
|
||||
cudaGetDevice( &whichDevice );
|
||||
cudaGetDeviceProperties( &prop, whichDevice );
|
||||
//debug code
|
||||
if (prop.canMapHostMemory != 1) {
|
||||
printf( "Device can not map memory.\n" );
|
||||
}
|
||||
|
||||
printf("L2 Cache size= %u \n",prop.l2CacheSize);
|
||||
printf("maxThreadsPerBlock= %u \n",prop.maxThreadsPerBlock);
|
||||
printf("maxGridSize= %i \n",prop.maxGridSize[0]);
|
||||
printf("sharedMemPerBlock= %lu \n",prop.sharedMemPerBlock);
|
||||
printf("deviceOverlap= %i \n",prop.deviceOverlap);
|
||||
//end debug code
|
||||
// findCudaDevice(argc, (const char **)argv);
|
||||
// cudaDeviceProp prop;
|
||||
// int num_devices, device;
|
||||
// cudaGetDeviceCount(&num_devices);
|
||||
// if (num_devices > 1) {
|
||||
// int max_multiprocessors = 0, max_device = 0;
|
||||
// for (device = 0; device < num_devices; device++) {
|
||||
// cudaDeviceProp properties;
|
||||
// cudaGetDeviceProperties(&properties, device);
|
||||
// if (max_multiprocessors < properties.multiProcessorCount) {
|
||||
// max_multiprocessors = properties.multiProcessorCount;
|
||||
// max_device = device;
|
||||
// }
|
||||
// printf("Found GPU device # %i\n",device);
|
||||
// }
|
||||
// //cudaSetDevice(max_device);
|
||||
//
|
||||
// //set random device!
|
||||
// cudaSetDevice(rand() % num_devices); //generates a random number between 0 and num_devices to split the threads between GPUs
|
||||
//
|
||||
// cudaGetDeviceProperties( &prop, max_device );
|
||||
// //debug code
|
||||
// if (prop.canMapHostMemory != 1) {
|
||||
// printf( "Device can not map memory.\n" );
|
||||
// }
|
||||
// printf("L2 Cache size= %u \n",prop.l2CacheSize);
|
||||
// printf("maxThreadsPerBlock= %u \n",prop.maxThreadsPerBlock);
|
||||
// printf("maxGridSize= %i \n",prop.maxGridSize[0]);
|
||||
// printf("sharedMemPerBlock= %lu \n",prop.sharedMemPerBlock);
|
||||
// printf("deviceOverlap= %i \n",prop.deviceOverlap);
|
||||
// printf("multiProcessorCount= %i \n",prop.multiProcessorCount);
|
||||
// }else{
|
||||
// int whichDevice;
|
||||
// cudaGetDevice( &whichDevice );
|
||||
// cudaGetDeviceProperties( &prop, whichDevice );
|
||||
// //debug code
|
||||
// if (prop.canMapHostMemory != 1) {
|
||||
// printf( "Device can not map memory.\n" );
|
||||
// }
|
||||
//
|
||||
// printf("L2 Cache size= %u \n",prop.l2CacheSize);
|
||||
// printf("maxThreadsPerBlock= %u \n",prop.maxThreadsPerBlock);
|
||||
// printf("maxGridSize= %i \n",prop.maxGridSize[0]);
|
||||
// printf("sharedMemPerBlock= %lu \n",prop.sharedMemPerBlock);
|
||||
// printf("deviceOverlap= %i \n",prop.deviceOverlap);
|
||||
// printf("multiProcessorCount= %i \n",prop.multiProcessorCount);
|
||||
// }
|
||||
|
||||
//checkCudaErrors(cudaFuncSetCacheConfig(CUDA_32fc_x2_multiply_x2_dot_prod_32fc_, cudaFuncCachePreferShared));
|
||||
|
||||
@ -300,7 +410,7 @@ bool cuda_multicorrelator::init_cuda(const int argc, const char **argv, int sign
|
||||
// Required: The last correlator tap in d_shifts_samples has the largest sample shift
|
||||
size_t size_local_code_bytes = local_codes_length_samples * sizeof(GPU_Complex);
|
||||
checkCudaErrors(cudaMalloc((void **)&d_local_codes_in, size_local_code_bytes));
|
||||
checkCudaErrors(cudaMalloc((void **)&d_shifts_samples, size+sizeof(int)*n_correlators));
|
||||
checkCudaErrors(cudaMalloc((void **)&d_shifts_samples, sizeof(int)*n_correlators));
|
||||
|
||||
//scalars
|
||||
checkCudaErrors(cudaMalloc((void **)&d_corr_out, sizeof(std::complex<float>)*n_correlators));
|
||||
@ -315,6 +425,116 @@ bool cuda_multicorrelator::init_cuda(const int argc, const char **argv, int sign
|
||||
}
|
||||
|
||||
|
||||
bool cuda_multicorrelator::init_cuda_integrated_resampler(
|
||||
const int argc, const char **argv,
|
||||
int signal_length_samples,
|
||||
int code_length_chips,
|
||||
int n_correlators
|
||||
)
|
||||
{
|
||||
// use command-line specified CUDA device, otherwise use device with highest Gflops/s
|
||||
// findCudaDevice(argc, (const char **)argv);
|
||||
// cudaDeviceProp prop;
|
||||
// int num_devices, device;
|
||||
// cudaGetDeviceCount(&num_devices);
|
||||
// if (num_devices > 1) {
|
||||
// int max_multiprocessors = 0, max_device = 0;
|
||||
// for (device = 0; device < num_devices; device++) {
|
||||
// cudaDeviceProp properties;
|
||||
// cudaGetDeviceProperties(&properties, device);
|
||||
// if (max_multiprocessors < properties.multiProcessorCount) {
|
||||
// max_multiprocessors = properties.multiProcessorCount;
|
||||
// max_device = device;
|
||||
// }
|
||||
// printf("Found GPU device # %i\n",device);
|
||||
// }
|
||||
// //cudaSetDevice(max_device);
|
||||
//
|
||||
// //set random device!
|
||||
// cudaSetDevice(rand() % num_devices); //generates a random number between 0 and num_devices to split the threads between GPUs
|
||||
//
|
||||
// cudaGetDeviceProperties( &prop, max_device );
|
||||
// //debug code
|
||||
// if (prop.canMapHostMemory != 1) {
|
||||
// printf( "Device can not map memory.\n" );
|
||||
// }
|
||||
// printf("L2 Cache size= %u \n",prop.l2CacheSize);
|
||||
// printf("maxThreadsPerBlock= %u \n",prop.maxThreadsPerBlock);
|
||||
// printf("maxGridSize= %i \n",prop.maxGridSize[0]);
|
||||
// printf("sharedMemPerBlock= %lu \n",prop.sharedMemPerBlock);
|
||||
// printf("deviceOverlap= %i \n",prop.deviceOverlap);
|
||||
// printf("multiProcessorCount= %i \n",prop.multiProcessorCount);
|
||||
// }else{
|
||||
// int whichDevice;
|
||||
// cudaGetDevice( &whichDevice );
|
||||
// cudaGetDeviceProperties( &prop, whichDevice );
|
||||
// //debug code
|
||||
// if (prop.canMapHostMemory != 1) {
|
||||
// printf( "Device can not map memory.\n" );
|
||||
// }
|
||||
//
|
||||
// printf("L2 Cache size= %u \n",prop.l2CacheSize);
|
||||
// printf("maxThreadsPerBlock= %u \n",prop.maxThreadsPerBlock);
|
||||
// printf("maxGridSize= %i \n",prop.maxGridSize[0]);
|
||||
// printf("sharedMemPerBlock= %lu \n",prop.sharedMemPerBlock);
|
||||
// printf("deviceOverlap= %i \n",prop.deviceOverlap);
|
||||
// printf("multiProcessorCount= %i \n",prop.multiProcessorCount);
|
||||
// }
|
||||
|
||||
//checkCudaErrors(cudaFuncSetCacheConfig(CUDA_32fc_x2_multiply_x2_dot_prod_32fc_, cudaFuncCachePreferShared));
|
||||
|
||||
// ALLOCATE GPU MEMORY FOR INPUT/OUTPUT and INTERNAL vectors
|
||||
|
||||
size_t size = signal_length_samples * sizeof(GPU_Complex);
|
||||
|
||||
checkCudaErrors(cudaMalloc((void **)&d_sig_in, size));
|
||||
checkCudaErrors(cudaMemset(d_sig_in,0,size));
|
||||
|
||||
//checkCudaErrors(cudaMalloc((void **)&d_nco_in, size));
|
||||
checkCudaErrors(cudaMalloc((void **)&d_sig_doppler_wiped, size));
|
||||
checkCudaErrors(cudaMemset(d_sig_doppler_wiped,0,size));
|
||||
|
||||
checkCudaErrors(cudaMalloc((void **)&d_local_codes_in, sizeof(std::complex<float>)*code_length_chips));
|
||||
checkCudaErrors(cudaMemset(d_local_codes_in,0,sizeof(std::complex<float>)*code_length_chips));
|
||||
|
||||
d_code_length_chips=code_length_chips;
|
||||
|
||||
checkCudaErrors(cudaMalloc((void **)&d_shifts_chips, sizeof(float)*n_correlators));
|
||||
checkCudaErrors(cudaMemset(d_shifts_chips,0,sizeof(float)*n_correlators));
|
||||
|
||||
//scalars
|
||||
checkCudaErrors(cudaMalloc((void **)&d_corr_out, sizeof(std::complex<float>)*n_correlators));
|
||||
checkCudaErrors(cudaMemset(d_corr_out,0,sizeof(std::complex<float>)*n_correlators));
|
||||
|
||||
// Launch the Vector Add CUDA Kernel
|
||||
threadsPerBlock = 256;
|
||||
blocksPerGrid =(int)(signal_length_samples+threadsPerBlock-1)/threadsPerBlock;
|
||||
|
||||
cudaStreamCreate (&stream1) ;
|
||||
cudaStreamCreate (&stream2) ;
|
||||
return true;
|
||||
}
|
||||
|
||||
bool cuda_multicorrelator::set_local_code_and_taps(
|
||||
int code_length_chips,
|
||||
const std::complex<float>* local_codes_in,
|
||||
float *shifts_chips,
|
||||
int n_correlators
|
||||
)
|
||||
{
|
||||
// local code CPU -> GPU copy memory
|
||||
checkCudaErrors(cudaMemcpyAsync(d_local_codes_in, local_codes_in, sizeof(GPU_Complex)*code_length_chips, cudaMemcpyHostToDevice,stream1));
|
||||
d_code_length_chips=(float)code_length_chips;
|
||||
|
||||
// Correlator shifts vector CPU -> GPU copy memory (fractional chip shifts are allowed!)
|
||||
checkCudaErrors(cudaMemcpyAsync(d_shifts_chips, shifts_chips, sizeof(float)*n_correlators,
|
||||
cudaMemcpyHostToDevice,stream1));
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
|
||||
bool cuda_multicorrelator::Carrier_wipeoff_multicorrelator_cuda(
|
||||
std::complex<float>* corr_out,
|
||||
const std::complex<float>* sig_in,
|
||||
@ -396,13 +616,88 @@ bool cuda_multicorrelator::Carrier_wipeoff_multicorrelator_cuda(
|
||||
return true;
|
||||
}
|
||||
|
||||
bool cuda_multicorrelator::Carrier_wipeoff_multicorrelator_resampler_cuda(
|
||||
std::complex<float>* corr_out,
|
||||
const std::complex<float>* sig_in,
|
||||
float rem_carrier_phase_in_rad,
|
||||
float phase_step_rad,
|
||||
float code_phase_step_chips,
|
||||
float rem_code_phase_chips,
|
||||
int signal_length_samples,
|
||||
int n_correlators)
|
||||
{
|
||||
|
||||
size_t memSize = signal_length_samples * sizeof(std::complex<float>);
|
||||
// input signal CPU -> GPU copy memory
|
||||
checkCudaErrors(cudaMemcpyAsync(d_sig_in, sig_in, memSize,
|
||||
cudaMemcpyHostToDevice, stream2));
|
||||
|
||||
//***** NOTICE: NCO is computed on-the-fly, not need to copy NCO into GPU! ****
|
||||
|
||||
//Launch carrier wipe-off kernel here, while local codes are being copied to GPU!
|
||||
checkCudaErrors(cudaStreamSynchronize(stream2));
|
||||
|
||||
CUDA_32fc_Doppler_wipeoff<<<blocksPerGrid, threadsPerBlock,0, stream2>>>(d_sig_doppler_wiped, d_sig_in,rem_carrier_phase_in_rad,phase_step_rad, signal_length_samples);
|
||||
|
||||
//wait for Doppler wipeoff end...
|
||||
checkCudaErrors(cudaStreamSynchronize(stream1));
|
||||
checkCudaErrors(cudaStreamSynchronize(stream2));
|
||||
|
||||
//launch the multitap correlator with integrated local code resampler!
|
||||
|
||||
scalarProdGPUCPXxN_shifts_chips<<<blocksPerGrid, threadsPerBlock,0 ,stream1>>>(
|
||||
d_corr_out,
|
||||
d_sig_doppler_wiped,
|
||||
d_local_codes_in,
|
||||
d_shifts_chips,
|
||||
d_code_length_chips,
|
||||
code_phase_step_chips,
|
||||
rem_code_phase_chips,
|
||||
n_correlators,
|
||||
signal_length_samples
|
||||
);
|
||||
|
||||
checkCudaErrors(cudaGetLastError());
|
||||
//wait for correlators end...
|
||||
checkCudaErrors(cudaStreamSynchronize(stream1));
|
||||
// Copy the device result vector in device memory to the host result vector
|
||||
// in host memory.
|
||||
|
||||
//scalar products (correlators outputs)
|
||||
checkCudaErrors(cudaMemcpyAsync(corr_out, d_corr_out, sizeof(std::complex<float>)*n_correlators,
|
||||
cudaMemcpyDeviceToHost,stream1));
|
||||
checkCudaErrors(cudaStreamSynchronize(stream1));
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
cuda_multicorrelator::cuda_multicorrelator()
|
||||
{
|
||||
d_sig_in=NULL;
|
||||
d_nco_in=NULL;
|
||||
d_sig_doppler_wiped=NULL;
|
||||
d_local_codes_in=NULL;
|
||||
d_shifts_samples=NULL;
|
||||
d_shifts_chips=NULL;
|
||||
d_corr_out=NULL;
|
||||
threadsPerBlock=0;
|
||||
blocksPerGrid=0;
|
||||
d_code_length_chips=0;
|
||||
}
|
||||
|
||||
bool cuda_multicorrelator::free_cuda()
|
||||
{
|
||||
// Free device global memory
|
||||
cudaFree(d_sig_in);
|
||||
//cudaFree(d_nco_in);
|
||||
cudaFree(d_local_codes_in);
|
||||
cudaFree(d_corr_out);
|
||||
if (d_sig_in!=NULL) cudaFree(d_sig_in);
|
||||
if (d_nco_in!=NULL) cudaFree(d_nco_in);
|
||||
if (d_sig_doppler_wiped!=NULL) cudaFree(d_sig_doppler_wiped);
|
||||
if (d_local_codes_in!=NULL) cudaFree(d_local_codes_in);
|
||||
if (d_corr_out!=NULL) cudaFree(d_corr_out);
|
||||
|
||||
|
||||
if (d_shifts_samples!=NULL) cudaFree(d_shifts_samples);
|
||||
if (d_shifts_chips!=NULL) cudaFree(d_shifts_chips);
|
||||
|
||||
|
||||
cudaStreamDestroy(stream1) ;
|
||||
cudaStreamDestroy(stream2) ;
|
||||
|
||||
@ -113,8 +113,20 @@ struct GPU_Complex_Short {
|
||||
class cuda_multicorrelator
|
||||
{
|
||||
public:
|
||||
cuda_multicorrelator();
|
||||
bool init_cuda(const int argc, const char **argv, int signal_length_samples, int local_codes_length_samples, int n_correlators);
|
||||
|
||||
bool init_cuda_integrated_resampler(
|
||||
const int argc, const char **argv,
|
||||
int signal_length_samples,
|
||||
int code_length_chips,
|
||||
int n_correlators
|
||||
);
|
||||
bool set_local_code_and_taps(
|
||||
int code_length_chips,
|
||||
const std::complex<float>* local_codes_in,
|
||||
float *shifts_chips,
|
||||
int n_correlators
|
||||
);
|
||||
bool free_cuda();
|
||||
bool Carrier_wipeoff_multicorrelator_cuda(
|
||||
std::complex<float>* corr_out,
|
||||
@ -125,6 +137,15 @@ public:
|
||||
const int *shifts_samples,
|
||||
int signal_length_samples,
|
||||
int n_correlators);
|
||||
bool Carrier_wipeoff_multicorrelator_resampler_cuda(
|
||||
std::complex<float>* corr_out,
|
||||
const std::complex<float>* sig_in,
|
||||
float rem_carrier_phase_in_rad,
|
||||
float phase_step_rad,
|
||||
float code_phase_step_chips,
|
||||
float rem_code_phase_chips,
|
||||
int signal_length_samples,
|
||||
int n_correlators);
|
||||
private:
|
||||
// Allocate the device input vectors
|
||||
GPU_Complex *d_sig_in;
|
||||
@ -133,6 +154,9 @@ private:
|
||||
GPU_Complex *d_local_codes_in;
|
||||
GPU_Complex *d_corr_out;
|
||||
int *d_shifts_samples;
|
||||
float *d_shifts_chips;
|
||||
float d_code_length_chips;
|
||||
|
||||
int threadsPerBlock;
|
||||
int blocksPerGrid;
|
||||
|
||||
|
||||
@ -94,7 +94,7 @@ Tracking_2nd_PLL_filter::Tracking_2nd_PLL_filter ()
|
||||
{
|
||||
//--- PLL variables --------------------------------------------------------
|
||||
d_pdi_carr = 0.001;// Summation interval for carrier
|
||||
d_plldampingratio = 0.65;
|
||||
d_plldampingratio = 0.7;
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -18,6 +18,7 @@
|
||||
|
||||
if(ENABLE_CUDA)
|
||||
FIND_PACKAGE(CUDA REQUIRED)
|
||||
add_definitions(-DCUDA_GPU_ACCEL=1)
|
||||
endif(ENABLE_CUDA)
|
||||
|
||||
set(GNSS_RECEIVER_SOURCES
|
||||
|
||||
@ -1610,12 +1610,14 @@ std::unique_ptr<TrackingInterface> GNSSBlockFactory::GetTrkBlock(
|
||||
out_streams, queue));
|
||||
block = std::move(block_);
|
||||
}
|
||||
#if CUDA_GPU_ACCEL
|
||||
else if (implementation.compare("GPS_L1_CA_DLL_PLL_Tracking_GPU") == 0)
|
||||
{
|
||||
std::unique_ptr<TrackingInterface> block_(new GpsL1CaDllPllTrackingGPU(configuration.get(), role, in_streams,
|
||||
out_streams, queue));
|
||||
block = std::move(block_);
|
||||
}
|
||||
#endif
|
||||
else
|
||||
{
|
||||
// Log fatal. This causes execution to stop.
|
||||
|
||||
@ -33,6 +33,12 @@ if(ENABLE_UHD)
|
||||
set(GNSS_SDR_OPTIONAL_HEADERS ${GNSS_SDR_OPTIONAL_HEADERS} ${UHD_INCLUDE_DIRS})
|
||||
endif(ENABLE_UHD)
|
||||
|
||||
if(ENABLE_CUDA)
|
||||
FIND_PACKAGE(CUDA REQUIRED)
|
||||
add_definitions(-DCUDA_GPU_ACCEL=1)
|
||||
endif(ENABLE_CUDA)
|
||||
|
||||
|
||||
include_directories(
|
||||
${CMAKE_SOURCE_DIR}/src/core/system_parameters
|
||||
${CMAKE_SOURCE_DIR}/src/core/interfaces
|
||||
@ -48,6 +54,7 @@ include_directories(
|
||||
${GNURADIO_RUNTIME_INCLUDE_DIRS}
|
||||
${GNSS_SDR_OPTIONAL_HEADERS}
|
||||
${VOLK_GNSSSDR_INCLUDE_DIRS}
|
||||
${CUDA_INCLUDE_DIRS}
|
||||
)
|
||||
|
||||
add_definitions( -DGNSS_SDR_VERSION="${VERSION}" )
|
||||
@ -79,6 +86,7 @@ target_link_libraries(gnss-sdr ${MAC_LIBRARIES}
|
||||
${GNSS_SDR_OPTIONAL_LIBS}
|
||||
gnss_sp_libs
|
||||
gnss_rx
|
||||
${CUDA_LIBRARIES}
|
||||
)
|
||||
|
||||
|
||||
|
||||
@ -68,6 +68,11 @@
|
||||
#include "sbas_ephemeris.h"
|
||||
#include "sbas_time.h"
|
||||
|
||||
#if CUDA_GPU_ACCEL
|
||||
// For the CUDA runtime routines (prefixed with "cuda_")
|
||||
#include <cuda_runtime.h>
|
||||
#endif
|
||||
|
||||
|
||||
using google::LogMessage;
|
||||
|
||||
@ -143,6 +148,17 @@ int main(int argc, char** argv)
|
||||
google::ParseCommandLineFlags(&argc, &argv, true);
|
||||
std::cout << "Initializing GNSS-SDR v" << gnss_sdr_version << " ... Please wait." << std::endl;
|
||||
|
||||
#if CUDA_GPU_ACCEL
|
||||
// Reset the device
|
||||
// cudaDeviceReset causes the driver to clean up all state. While
|
||||
// not mandatory in normal operation, it is good practice. It is also
|
||||
// needed to ensure correct operation when the application is being
|
||||
// profiled. Calling cudaDeviceReset causes all profile data to be
|
||||
// flushed before the application exits
|
||||
cudaDeviceReset();
|
||||
std::cout << "Reset CUDA device done " << std::endl;
|
||||
#endif
|
||||
|
||||
if(GOOGLE_STRIP_LOG == 0)
|
||||
{
|
||||
google::InitGoogleLogging(argv[0]);
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user