RC1 NEON programming

This course explains how to use NEON SIMD instructions to boost multimedia algorithms


Objectives
	This course has been designed for programmers wanting to run multimedia algorithms on NEON Single Instruction Multiple Data execute units.
	Each instruction family is detailed, first at assembly level, and then at C level using macros developed present in arm_neon.h file.
	Several tricky usage of processing instructions are provided.
	Vector and vector element load / store instructions are studied and guidelines for organizing data in memory are provided to minimize the number of memory accesses.
	The underlying cache operation as well as preload mechanisms (instruction and hardware prefetch) are detailed to explain how a processing can be pipelined .
	The course shows how DSP typical algorithms such as FIR and FFT can be vectorized and then optimized to be executed on NEON unit.
	This course has already been delivered to companies developing audio applications for mobile phones.
	THIS COURSE IS PROPOSED EITHER AS AN INSTRUCTOR-LED COURSE OR AS E-LEARNING.
	ACSYS has developed an optimized NEON based FFT coded in assembler language
		performance for 1024 complex floating point single precision samples is:
		- 106_000 core clock cycles for Cortex-A9
		- 90_000 core clock cycles for Cortex-A8
		for any information contact guillaume.peron@ac6.fr
Labs are run under RVDS

A more detailed course description is available on request at info@ac6-training.com


Prerequisites
	Knowledge of ARM V4T / V5TE instruction set.

Plan


DAY 1
CORTEX-A8 AND CORTEX-A9(MP) ARCHITECTURE
	Data path, studying how data are loaded from external memory and copied into level 1 and possibly level 2 caches
	Programmer’s model
	Highlighting coherency issues when data are shared by several cores, purpose of the SCU implemented in Cortex-A9
	Cortex-A8 and Cortex-A9 instruction pipeline, branch predictors
INTRODUCTION TO NEON/VFPv3
	Clarifying the resources shared by NEON and VFP
	Register bank, Q registers, D registers
	Data types
	Vector vs scalar
	Related system registers
	Alignment issues
	Enabling NEON/VFP
NEON INSTRUCTION SYNTAX
	Instructions producing wider / narrower results
	Instructions modifiers
	Selecting the shape
	Selecting the operand / result type
	Syntax flexibility
	Declaring initialized vectors in C language
	Using unions with vectors and arrays of vectors to simplify the debug
	Casting vectors
LOAD / STORE INSTRUCTIONS
	Addressing modes
	Vector load / store
	Vector load / store multiple
	Element and structure load / store instructions
		Multiple single elements
		Single element to 1 lane
		Single elements to all lanes

	Optimizing the ordering of data in memory to take benefit of 2-, 3- and 4- element structures
		Example: managing audio samples

	Processor acceleration mechanisms: store merging buffers
		Practical lab: using load with de-interleaving instructions to store all right lane samples into a vector and left lane samples into another vector
DAY 2
DATA TRANSFER INSTRUCTIONS
	Move
	Swap
	Table lookup
	Vector transpose
	Vector zip / unzip
	Data transfer between NEON and integer unit
		Practical lab: clarifying narrow and long instructions, building a vector from bytes selected from a pair of vectors
LOGICAL AND BITFIELD INSTRUCTIONS
	Logical AND, Bit Clear, OR, XOR
	Operations with immediate values
	Bitwise insert instructions, avoiding branches
	Count Leading zeros, ones, signs
	Normalizing floating point numbers when VFP is not implemented
	Scalar duplicate
	Extract
	Shift with possible rounding and saturation
	Bitfield revers
		Practical lab: Transposing a matrix, shifting a large bitmap using vector instructions
ARITHMERICAL INSTRUCTIONS
	Add, modulo vs saturated arithmetic
	Halving / Doubling the result
	Rounding
	Subtract
	Multiply
	Multiply accumulate / Multiply subtract
	Absolute value
	Min / Max
	Converting Floating Point numbers into Fixed point numbers
	Converting Fixed point numbers into Floating point numbers
	Reciprocal estimate, reciprocal square root estimate, Newton-raphson algorithm
	Pairwise instructions
	Element comparison
		Practical lab: implementing a complex multiply accumulate with NEON
		Practical lab: converting fixed-point elements into single precision floating point values and adding the resulting elements
NEON CODING EXAMPLES
	FIR filter
		Converting the scalar algorithm into a vector algorithm
		Finding the NEON instructions to encode the vector algorithm
		Optimizing the code
		Using the performance monitor to tune the algorithm

	FFT (DFT)
		Converting the scalar algorithm into a vector algorithm, understanding how circle properties can be used to process 4 angles concurrently
		Finding the NEON instructions to encode the vector algorithm
		Optimizing the code
		Using the performance monitor to tune the algorithm

Durée	Prix	Calendrier
2 jours	1250 €