Practical vectorization Practical vectorization Sebastien Ponce sebastien.ponce@cern.ch CERN Thematic CERN School of Computing 2022 1/50 S.Ponce-CERN
Practical vectorization 1 / 50 S. Ponce - CERN Intro Measure Prereq Techniques Expectations Practical vectorization S´ebastien Ponce sebastien.ponce@cern.ch CERN Thematic CERN School of Computing 2022
Practical vectorization Outline Introduction ② Measuring vectorization Vectorization Prerequisite Vectorizing techniques in C++ ●Autovectorization oInline assembly o Intrinsics oCompiler extensions oLibraries What to expect 2/50 S.Ponce-CERN
Practical vectorization 2 / 50 S. Ponce - CERN Intro Measure Prereq Techniques Expectations Outline 1 Introduction 2 Measuring vectorization 3 Vectorization Prerequisite 4 Vectorizing techniques in C++ Autovectorization Inline assembly Intrinsics Compiler extensions Libraries 5 What to expect ?
Practical vectorization 4心，ntro Meature Peeeg Techniques Expectat66 Introduction Introduction Measuring vectorization Vectorization Prerequisite Vectorizing techniques in C+ What to e色pect? 3/50 S.Ponce-CERN
Practical vectorization 3 / 50 S. Ponce - CERN Intro Measure Prereq Techniques Expectations Introduction 1 Introduction 2 Measuring vectorization 3 Vectorization Prerequisite 4 Vectorizing techniques in C++ 5 What to expect ?
Practical vectorization Intro Meature Feeeg Technigues Expe Goal of this course Make the theory explained by Andrzej concerning SIMD and vectorization more concrete o Detail the impact of vectorization on your code on your data model 。on actual C++code Give an idea of what to expect from vectorized code 4/50 S.Ponce-CERN
Practical vectorization 4 / 50 S. Ponce - CERN Intro Measure Prereq Techniques Expectations Goal of this course Make the theory explained by Andrzej concerning SIMD and vectorization more concrete Detail the impact of vectorization on your code on your data model on actual C++code Give an idea of what to expect from vectorized code
Practical vectorization Intro SIMD Single Instruction Multiple Data Concept o Run the same operation in parallel on multiple data o Operation is as fast as in single data case oThe data leave in a "vector" Practically A B R +回=风 A2 B2 R2 → A B3 R3 A B R4 5/50 S.Ponce-CERN
Practical vectorization 5 / 50 S. Ponce - CERN Intro Measure Prereq Techniques Expectations SIMD - Single Instruction Multiple Data Concept Run the same operation in parallel on multiple data Operation is as fast as in single data case The data leave in a “vector” Practically A + B = R A 1 A 2 A 3 A 4 + B 1 B 2 B 3 B 4 = R 1 R 2 R 3 R 4