Micron’s Automata Processor

Presented by Jared Mistretta and Ryan Gault

Agenda

� Classical Computing Overview

� Automata Processing Introduction

� Micron’s Automata Processor Architect

� Micron’s Automata Processor Comparisons

� Micron’s Automata Processor Applications

Classical Computing - Architecture

Classical Computing – Execution Model

� F-D-X model

Classical Computing – Execution Model

� Methods for increasing FDX cycle rate� Increasing core clock frequencies� Decreasing memory latency� Pipelining operations� Multi-core and super-scalar architectures

� Problems with these scaling methods� Increases power consumption� Requires more expensive memory architectures� Pipelining is limited scalability� Programming complexity

Classical Computing – Memory Hierarchy

Classical Computing – Memory Hierarchy

Classical Computing – Inherent Problems

� Memory wall

� Sequential operations

� Energy efficiency/ cost of data movement

� Automata processor solves these problems

Automata Processor - Introduction

Automata Processor - Introduction

� Processing In Memory� For large unstructured datasets.� String Matching Machine

Automata Processor - Theory

� Nondeterministic finite state machine

� Ideal characteristics of highly efficient computing systems

� Small operands

� Operator efficiency

� Minimum operand movement

� Result efficiency

� Intrinsic parallelism

Automata Processor – Execution Model

Automata Processor – Computational Elements

� The State Transition Element (STE)

� The Counter Element

� The Boolean Element

Automata Processor – Computational Elements

Common aspects of the elements:1. Each receives sixteen inputs from the routing matrix.

2. Each performs a function within an automaton.

3. Each is programmable.

4. Each originates (drives) one signal back into the routing matrix.

Micron’s Automata Processor

Micron’s Automata Processor – STE

Micron’s Automata Processor –Character Class

Micron’s Automata Processor -Counter Element

Micron’s Automata Processor -Boolean Element

Micron’s Automata Processor -DRAM Comparison

Micron’s Automata Processor –DRAM Comparison

Micron’s Automata Processor –Routing Matrix

Micron’s Automata Processor -Comparisons

Micron’s Automata Processor -Comparisons

� FPGA� Both reconfigurable� Large scale Boolean logic� Control an array of automata processors

� GPU

� Automata threads works independently so the programmer does not have to focus on exploiting parallelism in GPU’s and CPU’s

Micron’s Automata Processor -Applications

� Heterogeneous computing

� Bioinformatics

� Network security

� Signal Intelligence and cryptography

� Finance

� Big Data Domain

Micron’s Automata Processor - Modules

Conclusion

� Micron’s Automata Processor solves complex problems� Solution to big data problems which are becoming more common