1、ARM上的OpenBLAS性能優(yōu)化技術(shù)什么是BLAS？lBasic Linear Algebra Subprogramsl基本線性代數(shù)子程序BLAS3級(jí)：矩陣-矩陣BLAS2級(jí)：矩陣-向量BLAS1級(jí)：向量-向量BLAS與深度學(xué)習(xí)lAlexnetOpenBLASl2011年，forked from Gotoblas2l全球最好的開(kāi)源矩陣計(jì)算庫(kù)l2016 中國(guó)計(jì)算機(jī)學(xué)會(huì)科技進(jìn)步二等獎(jiǎng)l進(jìn)入主流Linux發(fā)行版l進(jìn)入OpenHPC套件OpenBLASl支持主流CPU處理器Intel，AMDARM，AArch64MIPS，龍芯IBM Powerl支持常見(jiàn)操作系統(tǒng)LinuxWindowsMac OSX

2、FreeBSDAndroidOpenBLAS用戶OpenBLAS性能lIntel Sandy BridgeOpenBLAS性能l龍芯3AGEMM算法GEMM算法GEMM算法GEMM算法GEMM算法GEMM算法GEMM算法GEMM算法GEMM算法l核心匯編代碼寄存器分塊指令流水線SIMD，循環(huán)展開(kāi)，預(yù)取BLAS性能優(yōu)化流派l自動(dòng)調(diào)優(yōu) Auto- tuningATLAS快速開(kāi)發(fā)和移植性能一般l手工核心匯編GotoBLAS/Ope nBLAS性能好新架構(gòu)？Auto-tuning生存高效代碼？AUGEMlAutomatically Generate Efficient Matrix kernell目標(biāo)

3、：自動(dòng)生成BLAS中高效匯編l支持x86 ISASSE，AVX，AVX 2.0l支持ARMv7 ISANeonAUGEMl輸入類似C代碼片段l輸出高性能匯編l基于模版Template隱含手工優(yōu)化知識(shí)C級(jí)別Kernel優(yōu)化Input simple C code of gemm kernelOutput Optimized C code of gemm kernelTemplate識(shí)別Output Optimized C code of gemm kernelLoad: Load:tmp0 = ptr_A0; tmp1 = ptr_B0;Multiply: tmp2 = tmp0 * tmp1;

4、Add:res0 = res0 + tmp2;Load: tmp0 = Cj*LDC+i; Add:res0 = res0 + tmp0; Store: Cj*LDC+i = res0;Template識(shí)別l預(yù)定義6種Template2組Template優(yōu)化lSIMD向量化mmUnrolledCOMP(ptr_A,0,2,ptr_B,0,2,(res0,res1,res2,res3) mmCOMP(ptr_A,0,ptr_B,0,res0)1.tmp0 = ptr_A0; 2.tmp1 = ptr_B0; 3.tmp2 = tmp0 * tmp1; 4.res0 = res0 + tmp2;m

5、mCOMP(ptr_A,1,ptr_B,0,res1) 1.tmp0 = ptr_A1;2.tmp1 = ptr_B0; 3.tmp2 = tmp1 * tmp1; 4.res1 = res1 + tmp2;mmCOMP(ptr_A,0,ptr_B,1,res2) 1.tmp0 = ptr_A0;2.tmp1 = ptr_B1; 3.tmp2 = tmp0 * tmp1; 4.res2 = res2 + tmp2;mmCOMP(ptr_A,1,ptr_B,1,res3) 1.tmp0 = ptr_A1;2.tmp1 = ptr_B1; 3.tmp2 = tmp0 * tmp1; 4.res3

6、= res3 + tmp2;Vld ptr_A, 0, vec0Vdup ptr_B, 0, vec1Vmul vec0, vec1, vec2Vadd vec2, vec3, vec3Vld ptr_A, 0, vec4Vdup ptr_B, 1, vec5Vmul vec4, vec5, vec6Vadd vec6, vec7, vec7Template優(yōu)化l寄存器分配根據(jù)用途分組ABC中間結(jié)果不考慮寄存器溢出臨時(shí)保存到堆棧 XVld ptr_A, 0, vec0Vdup ptr_B, 0, vec1Vmul vec0, vec1, vec2Vadd vec2, vec3, vec3Vld

7、 ptr_A, 0, vec4Vdup ptr_B, 1, vec5Vmul vec4, vec5, vec6Vadd vec6, vec7, vec7Template優(yōu)化l匯編指令映射Vld ptr_A, 0, reg0Vdup ptr_B, 0, reg1Vmul reg0, reg1, reg2Vadd reg2, reg3, reg3Vld ptr_A, 0, reg4Vdup ptr_B, 1, reg5Vmul reg4, reg5, reg6Vadd reg6, reg7, reg7InstructionsSSEAVXVld array, offset, regVld offse

8、t(array),regVld offset(array),regVst reg, array, offsetVst offset(array),regVst offset(array),regVmul reg0,reg1,reg2Vadd reg2,reg3,reg3Vmov reg1,reg2Vmul reg0,reg1 Vadd reg1,reg3Vmul reg0,reg1,reg2Vadd reg2,reg3,reg3Vld 0(ptr_A), reg0Vdup 0(ptr_B), reg1Vmov reg1,reg2Vmul reg0, reg1Vadd reg1, reg3 6.

9、Vld 0(ptr_A), reg0Vdup 0(ptr_B), reg1Vmul reg0, reg1, reg2Vadd reg2, reg3, reg3 5.匯編生成l將剩余代碼生成匯編循環(huán)控制l保持寄存器分配的一致性引入reg_table全局記錄表Algorithm of Template OptimizerAUGEM性能測(cè)試AUGEM性能測(cè)試lDGEMM on Intel Sandy BridgeAUGEM性能測(cè)試lDGEMM on AMD PiledriverAUGEM性能測(cè)試lDGEMV （BLAS2級(jí)）AUGEM性能測(cè)試lDAXPY (BLAS1級(jí))PerfSGEMM on ARMl單精度SGEMMNeon SIMD指令與IEEE 754標(biāo)準(zhǔn)不一致Round mode (Flush to Zero)不影響深度學(xué)習(xí)的精度l AUGEM生成匯編代碼支持ARM特殊指令vmla.f32c, a, bdPerfSGEMM on