Central Processing Unit Architecture

Views:
 
Category: Education
     
 

Presentation Description

No description available.

Comments

Presentation Transcript

Central Processing Unit Architecture : 

Central Processing Unit Architecture Architecture overview Machine organization von Neumann Speeding up CPU operations multiple registers pipelining superscalar and VLIW CISC vs. RISC

Computer Architecture : 

Computer Architecture Major components of a computer Central Processing Unit (CPU) memory peripheral devices Architecture is concerned with internal structures of each interconnections speed and width relative speeds of components Want maximum execution speed Balance is often critical issue

Computer Architecture (continued) : 

Computer Architecture (continued) CPU performs arithmetic and logical operations synchronous operation may consider instruction set architecture how machine looks to a programmer detailed hardware design

Computer Architecture (continued) : 

Computer Architecture (continued) Memory stores programs and data organized as bit byte = 8 bits (smallest addressable location) word = 4 bytes (typically; machine dependent) instructions consist of operation codes and addresses oprn oprn oprn addr 1 addr 2 addr 3 addr 2 addr 1 addr 1

Computer Architecture (continued) : 

Computer Architecture (continued) Numeric data representations integer (exact representation) sign-magnitude 2’s complement negative values change 0 to 1, add 1 floating point (approximate representation) scientific notation: 0.3481 x 106 inherently imprecise IEEE Standard 754-1985 s magnitude s exp significand

Simple Machine Organization : 

Simple Machine Organization Institute for Advanced Studies machine (1947) “von Neumann machine” ALU performs transfers between memory and I/O devices note two instructions per memory word main memory Input- Output Equipment Arithmetic - Logic Unit Program Control Unit op code op code address address 0 8 20 28 39

Simple Machine Organization (continued) : 

Simple Machine Organization (continued) ALU does arithmetic and logical comparisons AC = accumulator holds results MQ = memory-quotient holds second portion of long results MBR = memory buffer register holds data while operation executes

Simple Machine Organization (continued) : 

Simple Machine Organization (continued) Program control determines what computer does based on instruction read from memory MAR = memory address register holds address of memory cell to be read PC = program counter; address of next instruction to be read IR = instruction register holds instruction being executed IBR holds right half of instruction read from memory

Simple Machine Organization (continued) : 

Simple Machine Organization (continued) Machine operates on fetch-execute cycle Fetch PC MAR read M(MAR) into MBR copy left and right instructions into IR and IBR Execute address part of IR MAR read M(MAR) into MBR execute opcode

Simple Machine Organization (continued) : 

Simple Machine Organization (continued)

Architecture Families : 

Architecture Families Before mid-60’s, every new machine had a different instruction set architecture programs from previous generation didn’t run on new machine cost of replacing software became too large IBM System/360 created family concept single instruction set architecture wide range of price and performance with same software Performance improvements based on different detailed implementations memory path width (1 byte to 8 bytes) faster, more complex CPU design greater I/O throughput and overlap “Software compatibility” now a major issue partially offset by high level language (HLL) software

Architecture Families : 

Architecture Families

Multiple Register Machines : 

Multiple Register Machines Initially, machines had only a few registers 2 to 8 or 16 common registers more expensive than memory Most instructions operated between memory locations results had to start from and end up in memory, so fewer instructions although more complex means smaller programs and (supposedly) faster execution fewer instructions and data to move between memory and ALU But registers are much faster than memory 30 times faster

Multiple Register Machines (continued) : 

Multiple Register Machines (continued) Also, many operands are reused within a short time waste time loading operand again the next time it’s needed Depending on mix of instructions and operand use, having many registers may lead to less traffic to memory and faster execution Most modern machines use a multiple register architecture maximum number about 512, common number 32 integer, 32 floating point

Pipelining : 

Pipelining One way to speed up CPU is to increase clock rate limitations on how fast clock can run to complete instruction Another way is to execute more than one instruction at one time

Pipelining : 

Pipelining Pipelining breaks instruction execution down into several stages put registers between stages to “buffer” data and control execute one instruction as first starts second stage, execute second instruction, etc. speedup same as number of stages as long as pipe is full

Pipelining (continued) : 

Pipelining (continued) Consider an example with 6 stages FI = fetch instruction DI = decode instruction CO = calculate location of operand FO = fetch operand EI = execute instruction WO = write operand (store result)

Pipelining Example : 

Pipelining Example Executes 9 instructions in 14 cycles rather than 54 for sequential execution

Pipelining (continued) : 

Pipelining (continued) Hazards to pipelining conditional jump instruction 3 branches to instruction 15 pipeline must be flushed and restarted later instruction needs operand being calculated by instruction still in pipeline pipeline stalls until result ready

Pipelining Problem Example : 

Pipelining Problem Example Is this really a problem?

Real-life Problem : 

Real-life Problem Not all instructions execute in one clock cycle floating point takes longer than integer fp divide takes longer than fp multiply which takes longer than fp add typical values integer add/subtract 1 memory reference 1 fp add 2 (make 2 stages) fp (or integer) multiply 6 (make 2 stages) fp (or integer) divide 15 Break floating point unit into a sub-pipeline execute up to 6 instructions at once

Pipelining (continued) : 

Pipelining (continued) This is not simple to implement note all 6 instructions could finish at the same time!!

More Speedup : 

More Speedup Pipelined machines issue one instruction each clock cycle how to speed up CPU even more? Issue more than one instruction per clock cycle

Superscalar Architectures : 

Superscalar Architectures Superscalar machines issue a variable number of instructions each clock cycle, up to some maximum instructions must satisfy some criteria of independence simple choice is maximum of one fp and one integer instruction per clock need separate execution paths for each possible simultaneous instruction issue compiled code from non-superscalar implementation of same architecture runs unchanged, but slower

Superscalar Example : 

Superscalar Example Each instruction path may be pipelined 0 2 3 4 5 6 7 8 1 clock

Superscalar Problem : 

Superscalar Problem Instruction-level parallelism what if two successive instructions can’t be executed in parallel? data dependencies, or two instructions of slow type Design machine to increase multiple execution opportunities

VLIW Architectures : 

VLIW Architectures Very Long Instruction Word (VLIW) architectures store several simple instructions in one long instruction fetched from memory number and type are fixed e.g., 2 memory reference, 2 floating point, one integer need one functional unit for each possible instruction 2 fp units, 1 integer unit, 2 MBRs all run synchronized each instruction is stored in a single word requires wider memory communication paths many instructions may be empty, meaning wasted code space

VLIW Example : 

VLIW Example

Instruction Level Parallelism : 

Instruction Level Parallelism Success of superscalar and VLIW machines depends on number of instructions that occur together that can be issued in parallel no dependencies no branches Compilers can help create parallelism Speculation techniques try to overcome branch problems assume branch is taken execute instructions but don’t let them store results until status of branch is known

CISC vs. RISC : 

CISC vs. RISC CISC = Complex Instruction Set Computer RISC = Reduced Instruction Set Computer

CISC vs. RISC (continued) : 

CISC vs. RISC (continued) Historically, machines tend to add features over time instruction opcodes IBM 70X, 70X0 series went from 24 opcodes to 185 in 10 years same time performance increased 30 times addressing modes special purpose registers Motivations are to improve efficiency, since complex instructions can be implemented in hardware and execute faster make life easier for compiler writers support more complex higher-level languages

CISC vs. RISC : 

CISC vs. RISC Examination of actual code indicated many of these features were not used RISC advocates proposed simple, limited instruction set large number of general purpose registers and mostly register operations optimized instruction pipeline Benefits should include faster execution of instructions commonly used faster design and implementation

CISC vs. RISC : 

CISC vs. RISC Comparing some architectures

CISC vs. RISC : 

CISC vs. RISC Which approach is right? Typically, RISC takes about 1/5 the design time but CISC have adopted RISC techniques

authorStream Live Help