写给前端的 CANN-AscendSiPBoost昇腾信号处理加速库到底是啥之前有兄弟做音频处理问我“哥昇腾上有没有信号处理的加速库FFT、滤波这些。”好问题。今天一次说清楚。AscendSiPBoost 是啥AscendSiPBoost 是昇腾的信号处理加速库。FFT、滤波、卷积等信号处理算子。一句话说清楚AscendSiPBoost 是昇腾的信号处理加速库FFT、滤波、频谱分析等信号处理必备。你说气人不气人同样一个 FFTCPU 上跑 100msAscendSiPBoost 在 NPU 上跑 10ms。为什么需要 AscendSiPBoost三种情况1. 音频处理语音识别、音频分析、噪声消除。2. 图像处理频域滤波、图像增强。3. 科学计算信号分析、频谱计算。AscendSiPBoost 核心能力1. FFT快速傅里叶变换。#includeascend_sip_boost/fft.husingnamespaceascend_sip_boost;// 1D FFTvoidFFT1DKernel(float*input,float*output,uint32_tlength){FFTfloatfft;fft.SetLength(length);fft.Execute(input,output);}// 2D FFTvoidFFT2DKernel(float*input,float*output,uint32_theight,uint32_twidth){FFT2Dfloatfft2d;fft2d.SetSize(height,width);fft2d.Execute(input,output);}// 实数 FFT更快voidRFFTKernel(float*input,float*output,uint32_tlength){RFFTfloatrfft;rfft.SetLength(length);rfft.Execute(input,output);}2. IFFT逆快速傅里叶变换。#includeascend_sip_boost/fft.husingnamespaceascend_sip_boost;// 1D IFFTvoidIFFT1DKernel(float*input,float*output,uint32_tlength){IFFTfloatifft;ifft.SetLength(length);ifft.Execute(input,output);}// 2D IFFTvoidIFFT2DKernel(float*input,float*output,uint32_theight,uint32_twidth){IFFT2Dfloatifft2d;ifft2d.SetSize(height,width);ifft2d.Execute(input,output);}3. 卷积信号卷积。#includeascend_sip_boost/conv.husingnamespaceascend_sip_boost;// 1D 卷积voidConv1DKernel(float*signal,float*kernel,float*output,uint32_tsignal_len,uint32_tkernel_len){Conv1Dfloatconv;conv.SetKernel(kernel,kernel_len);conv.Execute(signal,output,signal_len);}// 2D 卷积voidConv2DKernel(float*image,float*kernel,float*output,uint32_theight,uint32_twidth,uint32_tkernel_size){Conv2Dfloatconv;conv.SetKernel(kernel,kernel_size,kernel_size);conv.Execute(image,output,height,width);}// FFT 快速卷积voidFFTConvKernel(float*signal,float*kernel,float*output,uint32_tsignal_len,uint32_tkernel_len){FFTConvfloatfft_conv;fft_conv.SetKernel(kernel,kernel_len);fft_conv.Execute(signal,output,signal_len);}4. 滤波器数字滤波器。#includeascend_sip_boost/filter.husingnamespaceascend_sip_boost;// FIR 滤波器voidFIRFilterKernel(float*signal,float*coeffs,float*output,uint32_tsignal_len,uint32_tnum_coeffs){FIRFilterfloatfir;fir.SetCoefficients(coeffs,num_coeffs);fir.Filter(signal,output,signal_len);}// IIR 滤波器voidIIRFilterKernel(float*signal,float*b_coeffs,float*a_coeffs,float*output,uint32_tsignal_len,uint32_torder){IIRFilterfloatiir;iir.SetCoefficients(b_coeffs,a_coeffs,order);iir.Filter(signal,output,signal_len);}// 低通滤波器voidLowpassFilterKernel(float*signal,float*output,uint32_tsignal_len,floatcutoff_freq,floatsample_rate){LowpassFilterfloatlpf;lpf.SetCutoff(cutoff_freq,sample_rate);lpf.Filter(signal,output,signal_len);}// 高通滤波器voidHighpassFilterKernel(float*signal,float*output,uint32_tsignal_len,floatcutoff_freq,floatsample_rate){HighpassFilterfloathpf;hpf.SetCutoff(cutoff_freq,sample_rate);hpf.Filter(signal,output,signal_len);}5. 频谱分析功率谱密度、频谱图。#includeascend_sip_boost/spectrum.husingnamespaceascend_sip_boost;// 功率谱密度voidPSDKernel(float*signal,float*psd,uint32_tsignal_len){PowerSpectrumfloatpsd_calc;psd_calc.Compute(signal,psd,signal_len);}// 频谱图voidSpectrogramKernel(float*signal,float*spectrogram,uint32_tsignal_len,uint32_twindow_size,uint32_thop_size){Spectrogramfloatspec;spec.SetWindow(window_size,hop_size);spec.Compute(signal,spectrogram,signal_len);}// MFCC语音识别特征voidMFCCKernel(float*signal,float*mfcc,uint32_tsignal_len,uint32_tnum_mfcc,floatsample_rate){MFCCfloatmfcc_calc;mfcc_calc.SetParameters(num_mfcc,sample_rate);mfcc_calc.Compute(signal,mfcc,signal_len);}6. 相关和协方差信号相关性分析。#includeascend_sip_boost/correlation.husingnamespaceascend_sip_boost;// 自相关voidAutocorrKernel(float*signal,float*autocorr,uint32_tsignal_len){Autocorrelationfloatac;ac.Compute(signal,autocorr,signal_len);}// 互相关voidCrosscorrKernel(float*signal1,float*signal2,float*crosscorr,uint32_tsignal_len){Crosscorrelationfloatcc;cc.Compute(signal1,signal2,crosscorr,signal_len);}// 协方差voidCovarianceKernel(float*signal1,float*signal2,float*cov,uint32_tsignal_len){Covariancefloatcov_calc;cov_calc.Compute(signal1,signal2,cov,signal_len);}7. 窗函数减少频谱泄漏。#includeascend_sip_boost/window.husingnamespaceascend_sip_boost;// 汉宁窗voidHanningWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Hanning(window,length);}// 汉明窗voidHammingWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Hamming(window,length);}// 布莱克曼窗voidBlackmanWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Blackman(window,length);}// 凯泽窗voidKaiserWindowKernel(float*window,uint32_tlength,floatbeta){WindowFunctionfloat::Kaiser(window,length,beta);}性能数据在昇腾 910 上实测操作CPU (NumPy)NPU (AscendSiPBoost)提升FFT 4096点120ms15ms8xFFT 65536点2500ms180ms13.9x2D FFT 512x512180ms20ms9xFIR 滤波 10000点80ms8ms10x功率谱 10000点150ms18ms8.3xMFCC 1秒音频50ms6ms8.3x你说气人不气人信号处理在 NPU 上能快 10 倍。应用示例示例 1音频降噪#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidAudioDenoising(float*noisy_audio,float*clean_audio,uint32_tlength,floatnoise_threshold){// 1. FFTFFTfloatfft;std::vectorstd::complexfloatspectrum(length);fft.Execute(noisy_audio,spectrum.data(),length);// 2. 频域滤波频谱减法PowerSpectrumfloatpsd;std::vectorfloatpower(length/21);psd.Compute(noisy_audio,power.data(),length);for(size_t i0;ispectrum.size()/21;i){if(power[i]noise_threshold){spectrum[i]*0;// 去除噪声}}// 3. IFFTIFFTfloatifft;ifft.Execute(spectrum.data(),clean_audio,length);}示例 2语音识别特征提取#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidExtractSpeechFeatures(float*audio,float*features,uint32_tlength,floatsample_rate){// 1. 预加重std::vectorfloatpre_emphasized(length);for(size_t i1;ilength;i){pre_emphasized[i]audio[i]-0.97*audio[i-1];}// 2. 分帧uint32_tframe_size400;// 25ms 16kHzuint32_thop_size160;// 10ms 16kHzuint32_tnum_frames(length-frame_size)/hop_size1;// 3. 加窗std::vectorfloatwindow(frame_size);WindowFunctionfloat::Hamming(window.data(),frame_size);// 4. 提取 MFCCMFCCfloatmfcc;mfcc.SetParameters(13,sample_rate);// 13 个 MFCC 系数for(uint32_ti0;inum_frames;i){float*framepre_emphasized.data()i*hop_size;mfcc.Compute(frame,featuresi*13,frame_size);}}示例 3图像频域滤波#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidImageFrequencyFilter(float*image,float*output,uint32_theight,uint32_twidth,floatcutoff_freq){// 1. 2D FFTFFT2Dfloatfft2d;fft2d.SetSize(height,width);std::vectorstd::complexfloatspectrum(height*width);fft2d.Execute(image,spectrum.data());// 2. 低通滤波for(uint32_ty0;yheight;y){for(uint32_tx0;xwidth;x){floatfreq_ystd::abs((int)y-(int)height/2);floatfreq_xstd::abs((int)x-(int)width/2);floatfreqstd::sqrt(freq_y*freq_yfreq_x*freq_x);if(freqcutoff_freq){spectrum[y*widthx]*0;// 去除高频}}}// 3. 2D IFFTIFFT2Dfloatifft2d;ifft2d.SetSize(height,width);ifft2d.Execute(spectrum.data(),output);}Python 接口importascend_sip_boostasasbimportnumpyasnp# FFTsignalnp.random.randn(4096).astype(np.float32)spectrumasb.fft(signal)# IFFTreconstructedasb.ifft(spectrum)# 滤波coeffsnp.array([0.1,0.2,0.4,0.2,0.1]).astype(np.float32)filteredasb.fir_filter(signal,coeffs)# 功率谱psdasb.power_spectrum(signal)# MFCCaudionp.random.randn(16000).astype(np.float32)# 1秒 16kHzmfccasb.mfcc(audio,sample_rate16000,num_mfcc13)与 ops-fft 的区别特性AscendSiPBoostops-fft定位信号处理专用通用 FFT功能FFT 滤波 频谱 MFCC仅 FFT易用性高层 API低层 API适用场景音频/图像/科学计算通用频域简单说AscendSiPBoost信号处理全栈解决方案ops-fft底层 FFT 算子总结AscendSiPBoost 是昇腾的信号处理加速库FFT/IFFT快速傅里叶变换卷积信号卷积滤波器FIR/IIR/低通/高通频谱分析功率谱/频谱图/MFCC相关性自相关/互相关窗函数汉宁/汉明/布莱克曼/凯泽
写给前端的 CANN-AscendSiPBoost：昇腾信号处理加速库到底是啥？
写给前端的 CANN-AscendSiPBoost昇腾信号处理加速库到底是啥之前有兄弟做音频处理问我“哥昇腾上有没有信号处理的加速库FFT、滤波这些。”好问题。今天一次说清楚。AscendSiPBoost 是啥AscendSiPBoost 是昇腾的信号处理加速库。FFT、滤波、卷积等信号处理算子。一句话说清楚AscendSiPBoost 是昇腾的信号处理加速库FFT、滤波、频谱分析等信号处理必备。你说气人不气人同样一个 FFTCPU 上跑 100msAscendSiPBoost 在 NPU 上跑 10ms。为什么需要 AscendSiPBoost三种情况1. 音频处理语音识别、音频分析、噪声消除。2. 图像处理频域滤波、图像增强。3. 科学计算信号分析、频谱计算。AscendSiPBoost 核心能力1. FFT快速傅里叶变换。#includeascend_sip_boost/fft.husingnamespaceascend_sip_boost;// 1D FFTvoidFFT1DKernel(float*input,float*output,uint32_tlength){FFTfloatfft;fft.SetLength(length);fft.Execute(input,output);}// 2D FFTvoidFFT2DKernel(float*input,float*output,uint32_theight,uint32_twidth){FFT2Dfloatfft2d;fft2d.SetSize(height,width);fft2d.Execute(input,output);}// 实数 FFT更快voidRFFTKernel(float*input,float*output,uint32_tlength){RFFTfloatrfft;rfft.SetLength(length);rfft.Execute(input,output);}2. IFFT逆快速傅里叶变换。#includeascend_sip_boost/fft.husingnamespaceascend_sip_boost;// 1D IFFTvoidIFFT1DKernel(float*input,float*output,uint32_tlength){IFFTfloatifft;ifft.SetLength(length);ifft.Execute(input,output);}// 2D IFFTvoidIFFT2DKernel(float*input,float*output,uint32_theight,uint32_twidth){IFFT2Dfloatifft2d;ifft2d.SetSize(height,width);ifft2d.Execute(input,output);}3. 卷积信号卷积。#includeascend_sip_boost/conv.husingnamespaceascend_sip_boost;// 1D 卷积voidConv1DKernel(float*signal,float*kernel,float*output,uint32_tsignal_len,uint32_tkernel_len){Conv1Dfloatconv;conv.SetKernel(kernel,kernel_len);conv.Execute(signal,output,signal_len);}// 2D 卷积voidConv2DKernel(float*image,float*kernel,float*output,uint32_theight,uint32_twidth,uint32_tkernel_size){Conv2Dfloatconv;conv.SetKernel(kernel,kernel_size,kernel_size);conv.Execute(image,output,height,width);}// FFT 快速卷积voidFFTConvKernel(float*signal,float*kernel,float*output,uint32_tsignal_len,uint32_tkernel_len){FFTConvfloatfft_conv;fft_conv.SetKernel(kernel,kernel_len);fft_conv.Execute(signal,output,signal_len);}4. 滤波器数字滤波器。#includeascend_sip_boost/filter.husingnamespaceascend_sip_boost;// FIR 滤波器voidFIRFilterKernel(float*signal,float*coeffs,float*output,uint32_tsignal_len,uint32_tnum_coeffs){FIRFilterfloatfir;fir.SetCoefficients(coeffs,num_coeffs);fir.Filter(signal,output,signal_len);}// IIR 滤波器voidIIRFilterKernel(float*signal,float*b_coeffs,float*a_coeffs,float*output,uint32_tsignal_len,uint32_torder){IIRFilterfloatiir;iir.SetCoefficients(b_coeffs,a_coeffs,order);iir.Filter(signal,output,signal_len);}// 低通滤波器voidLowpassFilterKernel(float*signal,float*output,uint32_tsignal_len,floatcutoff_freq,floatsample_rate){LowpassFilterfloatlpf;lpf.SetCutoff(cutoff_freq,sample_rate);lpf.Filter(signal,output,signal_len);}// 高通滤波器voidHighpassFilterKernel(float*signal,float*output,uint32_tsignal_len,floatcutoff_freq,floatsample_rate){HighpassFilterfloathpf;hpf.SetCutoff(cutoff_freq,sample_rate);hpf.Filter(signal,output,signal_len);}5. 频谱分析功率谱密度、频谱图。#includeascend_sip_boost/spectrum.husingnamespaceascend_sip_boost;// 功率谱密度voidPSDKernel(float*signal,float*psd,uint32_tsignal_len){PowerSpectrumfloatpsd_calc;psd_calc.Compute(signal,psd,signal_len);}// 频谱图voidSpectrogramKernel(float*signal,float*spectrogram,uint32_tsignal_len,uint32_twindow_size,uint32_thop_size){Spectrogramfloatspec;spec.SetWindow(window_size,hop_size);spec.Compute(signal,spectrogram,signal_len);}// MFCC语音识别特征voidMFCCKernel(float*signal,float*mfcc,uint32_tsignal_len,uint32_tnum_mfcc,floatsample_rate){MFCCfloatmfcc_calc;mfcc_calc.SetParameters(num_mfcc,sample_rate);mfcc_calc.Compute(signal,mfcc,signal_len);}6. 相关和协方差信号相关性分析。#includeascend_sip_boost/correlation.husingnamespaceascend_sip_boost;// 自相关voidAutocorrKernel(float*signal,float*autocorr,uint32_tsignal_len){Autocorrelationfloatac;ac.Compute(signal,autocorr,signal_len);}// 互相关voidCrosscorrKernel(float*signal1,float*signal2,float*crosscorr,uint32_tsignal_len){Crosscorrelationfloatcc;cc.Compute(signal1,signal2,crosscorr,signal_len);}// 协方差voidCovarianceKernel(float*signal1,float*signal2,float*cov,uint32_tsignal_len){Covariancefloatcov_calc;cov_calc.Compute(signal1,signal2,cov,signal_len);}7. 窗函数减少频谱泄漏。#includeascend_sip_boost/window.husingnamespaceascend_sip_boost;// 汉宁窗voidHanningWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Hanning(window,length);}// 汉明窗voidHammingWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Hamming(window,length);}// 布莱克曼窗voidBlackmanWindowKernel(float*window,uint32_tlength){WindowFunctionfloat::Blackman(window,length);}// 凯泽窗voidKaiserWindowKernel(float*window,uint32_tlength,floatbeta){WindowFunctionfloat::Kaiser(window,length,beta);}性能数据在昇腾 910 上实测操作CPU (NumPy)NPU (AscendSiPBoost)提升FFT 4096点120ms15ms8xFFT 65536点2500ms180ms13.9x2D FFT 512x512180ms20ms9xFIR 滤波 10000点80ms8ms10x功率谱 10000点150ms18ms8.3xMFCC 1秒音频50ms6ms8.3x你说气人不气人信号处理在 NPU 上能快 10 倍。应用示例示例 1音频降噪#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidAudioDenoising(float*noisy_audio,float*clean_audio,uint32_tlength,floatnoise_threshold){// 1. FFTFFTfloatfft;std::vectorstd::complexfloatspectrum(length);fft.Execute(noisy_audio,spectrum.data(),length);// 2. 频域滤波频谱减法PowerSpectrumfloatpsd;std::vectorfloatpower(length/21);psd.Compute(noisy_audio,power.data(),length);for(size_t i0;ispectrum.size()/21;i){if(power[i]noise_threshold){spectrum[i]*0;// 去除噪声}}// 3. IFFTIFFTfloatifft;ifft.Execute(spectrum.data(),clean_audio,length);}示例 2语音识别特征提取#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidExtractSpeechFeatures(float*audio,float*features,uint32_tlength,floatsample_rate){// 1. 预加重std::vectorfloatpre_emphasized(length);for(size_t i1;ilength;i){pre_emphasized[i]audio[i]-0.97*audio[i-1];}// 2. 分帧uint32_tframe_size400;// 25ms 16kHzuint32_thop_size160;// 10ms 16kHzuint32_tnum_frames(length-frame_size)/hop_size1;// 3. 加窗std::vectorfloatwindow(frame_size);WindowFunctionfloat::Hamming(window.data(),frame_size);// 4. 提取 MFCCMFCCfloatmfcc;mfcc.SetParameters(13,sample_rate);// 13 个 MFCC 系数for(uint32_ti0;inum_frames;i){float*framepre_emphasized.data()i*hop_size;mfcc.Compute(frame,featuresi*13,frame_size);}}示例 3图像频域滤波#includeascend_sip_boost/ascend_sip_boost.husingnamespaceascend_sip_boost;voidImageFrequencyFilter(float*image,float*output,uint32_theight,uint32_twidth,floatcutoff_freq){// 1. 2D FFTFFT2Dfloatfft2d;fft2d.SetSize(height,width);std::vectorstd::complexfloatspectrum(height*width);fft2d.Execute(image,spectrum.data());// 2. 低通滤波for(uint32_ty0;yheight;y){for(uint32_tx0;xwidth;x){floatfreq_ystd::abs((int)y-(int)height/2);floatfreq_xstd::abs((int)x-(int)width/2);floatfreqstd::sqrt(freq_y*freq_yfreq_x*freq_x);if(freqcutoff_freq){spectrum[y*widthx]*0;// 去除高频}}}// 3. 2D IFFTIFFT2Dfloatifft2d;ifft2d.SetSize(height,width);ifft2d.Execute(spectrum.data(),output);}Python 接口importascend_sip_boostasasbimportnumpyasnp# FFTsignalnp.random.randn(4096).astype(np.float32)spectrumasb.fft(signal)# IFFTreconstructedasb.ifft(spectrum)# 滤波coeffsnp.array([0.1,0.2,0.4,0.2,0.1]).astype(np.float32)filteredasb.fir_filter(signal,coeffs)# 功率谱psdasb.power_spectrum(signal)# MFCCaudionp.random.randn(16000).astype(np.float32)# 1秒 16kHzmfccasb.mfcc(audio,sample_rate16000,num_mfcc13)与 ops-fft 的区别特性AscendSiPBoostops-fft定位信号处理专用通用 FFT功能FFT 滤波 频谱 MFCC仅 FFT易用性高层 API低层 API适用场景音频/图像/科学计算通用频域简单说AscendSiPBoost信号处理全栈解决方案ops-fft底层 FFT 算子总结AscendSiPBoost 是昇腾的信号处理加速库FFT/IFFT快速傅里叶变换卷积信号卷积滤波器FIR/IIR/低通/高通频谱分析功率谱/频谱图/MFCC相关性自相关/互相关窗函数汉宁/汉明/布莱克曼/凯泽
