Review: Summary of Pipelining Basics
|
|
- Garey Montgomery
- 6 years ago
- Views:
Transcription
1 Review: ummary of Pipelining asics C152 Computer Architecture and Engineering Lecture 14 Pipelining Control Continued Introduction to Advanced Pipelining October 18, 1999 John Kubiatowicz (http.cs.berkeley.edu/~kubitron) Pipelines pass control information down the pipe just as data moves down pipe Foarding/talls handled by local control Hazards limit performance tructural: need more HW resources ata: need foarding, compiler scheduling Control: early evaluation &, delayed branch, prediction Increasing length of pipe increases impact of hazards; pipelining helps instruction bandwidth, not latency lecture slides: Lec14.1 Lec14.2 Recap: Pipeline Hazards Recap: Pipelined Processor for slides I-Fet ch C OpFetch OpFetch tore tructural Hazard IFetch C Inst. Valid cd ex ubbles talls Ex mem wb I-Fet ch C OpFetch Jump IF C EX IFetch C IF C EX IF C EX Control Hazard RAW (read after write) ata Hazard WAW ata Hazard (write after write) IF C OF Ex IF C OF Ex R WAR ata Hazard (write after read) Lec14.3 Next eparate control at each stage talls propagate backwards to freeze previous stages ubbles in pipeline introduced by placing Noops into local stage, stall previous stages. A ata. Equal Lec14.4
2 The ig Picture: Where are We Now The Five Classic Components of a Computer Processor Input Control ory atapath Output Recap: ata tationary Control The ain Control generates the control signals during /ec Control signals for (ExtOp, ALUrc,...) are used 1 cycle later Control signals for (Wr ranch) are used 2 cycles later Control signals for Wr (to Wr) are used 3 cycles later /ec Wr Today s Topics: Recap last lecture Review IP R3000 pipeline Administrivia Advanced Pipelining upercalar, VLIW/EPIC IF/I ister ain Control ExtOp ALUrc ALUOp st W ranch r to Wr I/Ex ister ExtOp ALUrc ALUOp st W ranch r to Wr Ex/ ister W rranch to Wr /Wr ister to Wr Lec14.5 Lec14.6 atapath + ata tationary Control Let s Try it Out Inst. fun op rs rt ecode rs rt v wb me ex im A v wb me v wb ata. 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 30 ori r8, r9, 17 these addresses are octal Next Lec14.7 Lec14.8
3 tart: Fetch 10 Inst. n n n n ecode rs rt im Fetch 14, ecode 10 Inst. lw r1, r2(3 ecode 2 rt n n n im Next A 10 ata IF. 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 30 ori r8, r9, 17 Next A 14 ata I IF. 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 30 ori r8, r9, 17 Lec14.9 Lec14.10 Fetch 20, ecode 14, 10 Inst. addi r2, r2, 3 ecode 2 rt lw r1 35 n n Fetch 24, ecode 20, 14, 10 Inst. sub r3, r4, r5 ecode 4 5 addi r2, r2, 3 3 lw r1 n Next r2 20 ata. EX 10 lw r1, r2(3 I 14 addi r2, r2, 3 IF 20 sub r3, r4, r5 30 ori r8, r9, 17 Next r2 24 r2+35 ata. 10 lw r1, r2(3 EX 14 addi r2, r2, 3 I 20 sub r3, r4, r5 IF 30 ori r8, r9, 17 Lec14.11 Lec14.12
4 Fetch 30, cd 24, Ex 20, 14, 10 Inst. beq r6, r7 100 ecode 6 7 Next sub r3 r4 r5 30 r2+3 ata Note elayed ranch: always execute ori after beq addi r2 lw r1 [r2+35]. 10 lw r1, r2(3 14 addi r2, r2, 3 EX 20 sub r3, r4, r5 I IF 30 ori r8, r9, 17 Lec14.13 Fetch 100, cd 30, Ex 24, 20, 14 Inst. ori r8, r9 17 ecode 9 xx Next beq 100 r6 r7 100 sub r3 r4-r5 addi r2 r2+3 ata. r1[r2+35] 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 EX I 30 ori r8, r9, 17 IF Lec14.14 Fetch 104, cd 100, Ex 30, 24, 20 Fetch 110, cd 104, Ex 100, 30, 24 Inst. ecode Inst. ecode Next ata. 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 EX 30 ori r8, r9, 17 Next ata. 10 lw r1, r2(3 14 addi r2, r2, 3 20 sub r3, r4, r5 30 ori r8, r9, 17 Fill it in yourself! I Lec14.15 Fill it in yourself! EX Lec14.16
5 Fetch 114, cd 110, Ex 104, 100, 30 Inst. ecode. Administrivia ail Lab 5 breakdowns to your TAs by tonight! Get started on Lab 5: Pipelining is difficult to get right! e sure that we will test gotcha cases in our mystery programs Wednesday: advanced pipelining Out-of-order execution/register renaming Reorder buffers ata 10 lw r1, r2(3 14 addi r2, r2, 3 Next 20 sub r3, r4, r5 30 ori r8, r9, 17 Fill it in yourself! Lec14.17 Lec14.18 Recap: ata Hazards Hazard etection Avoid some by design eliminate WAR by always fetching operands early (C) in pipe eleminate WAW by doing all s in order (last stage, static) etect and resolve remaining ones stall or foard (if possible) uppose instruction i is about to be issued and a predecessor instruction j is in the instruction pipeline. A RAW hazard exists on register ρ if ρ Rregs( i ) Wregs( j ) Keep a record of pending writes (for inst s in the pipe) and compare with operand regs of current instruction. When instruction issues, reserve its result register. When on operation completes, remove its write reservation. IF C EX RAW ata Hazard IF C EX WAW ata Hazard IF C EX IF C OF Ex IF C OF Ex R RAW ata Hazard A WAW hazard exists on register ρ if ρ Wregs( i ) Wregs( j ) A WAR hazard exists on register ρ if ρ Wregs( i ) Rregs( j ) Lec14.19 Lec14.20
6 Record of Pending Writes In Pipeline isters Resolve RAW by foarding (or bypassing) s alu mem m s IAU npc I mem op rs rt A im n op n op n op Current operand registers Pending writes hazard < ((rs ex) & regw ex ) OR ((rs mem) & regw me ) OR ((rs & regw wb) wb ) OR ((rt & regw ex) ex ) OR ((rt & regw mem) me ) OR ((rt wb ) & regw wb ) Lec14.21 s Foard mux alu mem m IAU npc I mem op rs rt A im n op n op n op s etect nearest valid write op operand register and foard into op latches, bypassing remainder of the pipe Increase muxes to add paths from pipeline registers ata Foarding ata ypassing Lec14.22 What about memory operations Compiler Avoiding Load talls: º If instructions are initiated in order and operations always occur in the same stage, there can be no hazards between memory operations! op Rd Ra Rb º What does delaying on arithmetic operations cost cycles hardware º What about data dependence on loads R1 <- R4 + R5 R2 <- [ R2 + I ] R3 <- R2 + R1 elayed Loads º Can recognize this in decode stage and introduce bubble while stalling fetch stage (hint for lab 5!) º Tricky situation: R1 <- [ R2 + I ] [R3+34] <- R1 Handle with bypass in memory stage! op Rd Ra Rb Rd Rd to reg file A T R scheduled unscheduled 54% gcc 31% 42% spice 14% 65% tex 25% 0% 20% 40% 60% 80% % loads stalling pipeline Lec14.23 Lec14.24
7 What about Interrupts, Traps, Faults External Interrupts: Allow pipeline to drain, Load with interrupt address Faults (within instruction, restartable) Force trap instruction into IF disable writes till trap hits must save multiple s or + state Recall: Precise Exceptions tate of the machine is preserved as if program executed up to the offending instruction All previous instructions completed Offending instruction and all following instructions act as if they have not even started ame system code will work on different implementations Exception/Interrupts: Implementation questions 5 instructions, executing in 5 different pipeline stages! Who caused the interrupt tage Problem interrupts occurring IF Page fault on instruction fetch; misaligned memory access; memory-protection violation I Undefined or illegal opcode EX Arithmetic exception E Page fault on data fetch; misaligned memory access; memory-protection violation; memory error How do we stop the pipeline How do we restart it o we interrupt immediately or wait How do we sort all of this out to maintain preciseness Lec14.25 Lec14.26 Exception Handling s alu mem m IAU npc I mem lw $2,20($ A im n op s Excp detect bad instruction address detect bad instruction Excp Excp Excp detect overflow detect bad data address Allow exception to take effect Lec14.27 Another look at the exception problem Time ata TL ad Inst Inst TL fault Overflow Program Flow IFetch cd Use pipeline to sort this out! IFetch cd IFetch cd Pass exception status along with instruction. Keep track of s for every instruction in pipeline. on t act on exception until it reache stage Handle interrupts through faulting noop in IF stage When instruction reaches end of E stage: ave E, Interrupt vector addr Turn all instructions in earlier stages into noops! IFetch cd Lec14.28
8 Resolution: Freeze above & ubble elow FYI: IP R3000 clocking discipline s IAU npc I mem op rs rt bubble freeze phi1 phi2 2-phase non-overlapping clocks Pipeline stage is two (level sensitive) latches A im n op alu mem m n op n op Flush accomplished by setting invalid bit in pipeline Edge-triggered phi1 phi2 phi1 s Lec14.29 Lec14.30 IP R3000 Instruction Pipeline Recall: ata Hazard on r1 Inst Fetch ecode. Read ALU / E.A ory Write TL I-Cache RF Operation Resource Usage TL I-cache RF TL ALUALU E.A. TL -Cache -Cache I n s t r. O r d e r Time (clock cycles) IF I/RF EX E add r1,r2,r3 sub r4,r1,r3 and r6,r1,r7 or r8,r1,r9 xor r10,r1,r11 ALU Im m ALU Im m ALU Im m Im ALU m ALU Im m Write in phase 1, read in phase 2 > eliminates bypass from With IP R3000 pipeline, no need to foard from stage Lec14.31 Lec14.32
9 IP R3000 ulticycle Operations Is CPI 1 for our pipeline op Rd Ra Rb Use control word of local stage to step through multicycle operation Remember that CPI is an Average # cycles/inst mul Rd Ra Rb A tall all stages above multicycle operation in the pipeline rain (bubble) stages below it IFetch cd IFetch cd IFetch cd Rd Rd to reg file Ex: ultiply, ivide, Cache iss R T Alternatively, launch multiply/divide to autonomous unit, only stall pipe if attempt to get result before ready - This means stall mflo/mfhi in decode stage if multiply/divide still executing - Extra credit in Lab 5 does this Lec14.33 CPI here is 1, since the average throughput is 1 instruction every cycle. What if there are stalls or multi-cycle execution Usually CPI > 1. How close can we get to 1 IFetch cd Lec14.34 Case tudy: IP R4000 (200 Hz) Case tudy: IP R tage Pipeline: IF first half of fetching of instruction; selection happens here as well as initiation of instruction cache access. I second half of access to instruction cache. RF instruction decode and register fetch, hazard checking and also instruction cache hit detection. EX execution, which includes effective address calculation, ALU operation, and branch target computation and condition evaluation. F data fetch, first half of access to data cache. second half of access to data cache. TC tag check, determine whether the data cache access hit. write back for loads and register-register operations. 8 tages: What is impact on Load delay ranch delay Why 7:2&\FOH /RG/WHQF\ 7+5((&\FOH %UQFK/WHQF\ FRQGLWLRQVHYOXWHG GXULQJKVH 'HO\VORWOXVWZRVWOOV %UQFKOLNHO\FQFHOVGHO\VORWLIQRWWNHQ '6 '6 7& '6 7& '6 :% 7& '6 :% 7& '6 Lec14.35 Lec14.36
10 IP R4000 Floating Point FP Adder, FP ultiplier, FP ivider Last step of FP ultiplier/ivider uses FP Adder HW 8 kinds of stages in FP units: tage Functional unit escription A FP adder antissa A stage FP divider ivide pipeline stage E FP multiplier Exception test stage FP multiplier First stage of multiplier N FP multiplier econd stage of multiplier R FP adder Rounding stage FP adder Operand shift stage U Unpack FP numbers IP FP Pipe tages FP Instr Add, ubtract U +A A+R R+ ultiply U E+ N N+A R ivide U A R 28 +A +R, +R, +A, +R, A, R quare root U E (A+R) 108 A R Negate U Absolute value U FP compare U A R tages: First stage of multiplier A antissa A stage N econd stage of multiplier ivide pipeline stage R Rounding stage E Exception test stage Operand shift stage U Unpack FP numbers Lec14.37 Lec14.38 R4000 Performance Improving Instruction Level Parallelism (ILP) Not ideal CPI of 1: Load stalls (1 or 2 clock cycles) ranch stalls (2 cycles + unfilled slots) FP result stalls: RAW data hazard (latency) FP structural stalls: Not enough FP hardware (parallelism) eqntott espresso gcc li doduc nasa7 ora spice2g6 su2cor tomcatv ILP: Overlap execution of unrelated instructions gcc 17% control transfer 5 instructions + 1 branch eyond single block to get more instruction level parallelism Loop level parallelism one opportunity First W, then HW approaches LX Floating Point as example easurements suggests R4000 performance FP execution has room for improvement ase Load stalls ranch stalls FP result stalls FP structural stalls Lec14.39 Lec14.40
11 FP Loop: Where are the Hazards Loop: L F0,0(R1) ;F0vector element A F4,F0,F2 ;add scalar from F2 0(R1),F4 ;store result UI R1,R1,8 ;decrement pointer 8 (W) NEZ R1,Loop ;branch R1!zero NOP ;delayed branch slot,qvwuxfwlrq,qvwuxfwlrq /WHQF\LQ URGXFLQJUHVXOW XVLQJUHVXOW FORFNF\FOHV )3$/8R $QRWKHU)3$/8R )3$/8R 6WRUHGRXEOH /RGGRXEOH )3$/8R /RGGRXEOH 6WRUHGRXEOH,QWHJHUR,QWHJHUR :KHUHUHWKHVWOOV" Lec14.41 FP Loop howing talls 1 Loop: L F0,0(R1) ;F0vector element 2 stall 3 A F4,F0,F2 ;add scalar in F2 4 stall 5 stall 6 0(R1),F4 ;store result 7 UI R1,R1,8 ;decrement pointer 8 (W) 8 NEZ R1,Loop ;branch R1!zero 9 stall ;delayed branch slot,qvwuxfwlrq,qvwuxfwlrq /WHQF\LQ URGXFLQJUHVXOW XVLQJUHVXOW FORFNF\FOHV )3$/8R $QRWKHU)3$/8R )3$/8R 6WRUHGRXEOH /RGGRXEOH )3$/8R 9 clocks: Rewrite code to minimize stalls Lec14.42 Revised FP Loop inimizing talls Unroll Loop Four Times (straightfoard way) 1 Loop: L F0,0(R1) 2 stall 3 A F4,F0,F2 4 UI R1,R1,8 5 NEZ R1,Loop ;delayed branch 6 8(R1),F4 ;altered when move past UI 6Z%1(QG6'E\FKQJLQJGGUHVVRI6',QVWUXFWLRQ,QVWUXFWLRQ /WHQF\LQ URGXFLQJUHVXOW XVLQJUHVXOW FORFNF\FOHV )3$/8R $QRWKHU)3$/8R )3$/8R 6WRUHGRXEOH /RGGRXEOH )3$/8R 6 clocks: Unroll loop 4 times code to make faster 1 Loop:L F0,0(R1) F\FOHVWOO 2 A F4,F0,F2 F\FOHVVWOO 3 0(R1),F4 ;drop UI & NEZ 4 L F6,-8(R1) 5 A F8,F6,F2 6-8(R1),F8 ;drop UI & NEZ 7 L F10,-16(R1) 8 A F12,F10,F2 9-16(R1),F12 ;drop UI & NEZ 10 L F14,-24(R1) 11 A F16,F14,F (R1),F16 13 UI R1,R1,#32 ;alter to 4*8 14 NEZ R1,LOOP 15 NOP Rewrite loop to minimize stalls [ FORFNF\FOHVRUHULWHUWLRQ $VVXPHV5LVPXOWLOHRI Lec14.43 Lec14.44
12 Unrolled Loop That inimizes talls Getting CPI < 1: Issuing ultiple Instructions/Cycle 1 Loop:L F0,0(R1) 2 L F6,-8(R1) 3 L F10,-16(R1) 4 L F14,-24(R1) 5 A F4,F0,F2 6 A F8,F6,F2 7 A F12,F10,F2 8 A F16,F14,F2 9 0(R1),F4 10-8(R1),F (R1),F12 12 UI R1,R1,#32 13 NEZ R1,LOOP 14 8(R1),F16 ; FORFNF\FOHVRUHULWHUWLRQ :KHQVIHWRPRYHLQVWUXFWLRQV" What assumptions made when moved code OK to move store past UI even though changes register OK to move loads before stores: get right data When is it safe for compiler to do such changes Two main variations: uperscalar and VLIW uperscalar: varying no. instructions/cycle (1 to 6) Parallelism and dependencies determined/resolved by HW I Power 604, un Ultraparc, EC Alpha 21164, HP 7100 Very Long Instruction Words (VLIW): fixed number of instructions (16) parallelism determined by compiler Pipeline is exposed; compiler must schedule delays to get right result Explicit Parallel Instruction Computer (EPIC)/ Intel 128 bit packets containing 3 instructions (can execute sequentially) Can link 128 bit packets together to allow more parallelism Compiler determines parallelism, HW checks dependencies and fowards/stalls Lec14.45 Lec14.46 Getting CPI < 1: Issuing ultiple Instructions/Cycle Unrolled Loop that inimizes talls for calar uperscalar LX: 2 instructions, 1 FP & 1 anything else Fetch 64-bits/clock cycle; Int on left, FP on right Can only issue 2nd instruction if 1st instruction issues ore ports for FP registers to do FP load & FP op in a pair Type Pipetages Int. instruction IF I EX E FP instruction IF I EX E Int. instruction IF I EX E FP instruction IF I EX E Int. instruction IF I EX E FP instruction IF I EX E 1 cycle load delay expands to 3 instructions in instruction in right half can t use it, nor instructions in next slot Lec Loop: L F0,0(R1) L to A: 1 Cycle 2 L F6,-8(R1) A to : 2 Cycles 3 L F10,-16(R1) 4 L F14,-24(R1) 5 A F4,F0,F2 6 A F8,F6,F2 7 A F12,F10,F2 8 A F16,F14,F2 9 0(R1),F4 10-8(R1),F (R1),F12 12 UI R1,R1,#32 13 NEZ R1,LOOP 14 8(R1),F16 ; clock cycles, or 3.5 per iteration Lec14.48
13 Loop Unrolling in uperscalar Limits of uperscalar Integer instruction FP instruction Clock cycle Loop: L F0,0(R1) 1 L F6,-8(R1) 2 L F10,-16(R1) A F4,F0,F2 3 L F14,-24(R1) A F8,F6,F2 4 L F18,-32(R1) A F12,F10,F2 5 0(R1),F4 A F16,F14,F2 6-8(R1),F8 A F20,F18,F2 7-16(R1),F (R1),F16 9 UI R1,R1,#40 10 NEZ R1,LOOP 11-32(R1),F20 12 Unrolled 5 times to avoid delays (+1 due to ) 12 clocks, or 2.4 clocks per iteration Lec14.49 While Integer/FP split is simple for the HW, get CPI of 0.5 only for programs with: Exactly 50% FP operations No hazards If more instructions issue at same time, greater difficulty of decode and issue Even 2-scalar > examine 2 opcodes, 6 register specifiers, & decide if 1 or 2 instructions can issue VLIW: tradeoff instruction space for simple decoding The long instruction word has room for many operations y definition, all the operations the compiler puts in the long instruction word can execute in parallel E.g., 2 integer operations, 2 FP ops, 2 ory refs, 1 branch - 16 to 24 bits per field > 7*16 or 112 bits to 7*24 or 168 bits wide Need compiling technique that schedules across several branches Lec14.50 Loop Unrolling in VLIW ory ory FP FP Int. op/ Clock reference 1 reference 2 operation 1 op. 2 branch L F0,0(R1) L F6,-8(R1) 1 L F10,-16(R1) L F14,-24(R1) 2 L F18,-32(R1) L F22,-40(R1) A F4,F0,F2 A F8,F6,F2 3 L F26,-48(R1) A F12,F10,F2 A F16,F14,F2 4 A F20,F18,F2 A F24,F22,F2 5 0(R1),F4-8(R1),F8 A F28,F26,F2 6-16(R1),F12-24(R1),F (R1),F20-40(R1),F24 UI R1,R1,#48 8-0(R1),F28 NEZ R1,LOOP 9 Unrolled 7 times to avoid delays 7 results in 9 clocks, or 1.3 clocks per iteration Need more registers in VLIW(EPIC > 128int + 128FP) oftware Pipelining Observation: if iterations from loops are independent, then can get more ILP by taking instructions from different iterations oftware pipelining: reorganizes loops so that each iteration is made from instructions chosen from different iterations of the original loop (- Tomasulo in W) oftwarepipelined iteration Iteration 0 Iteration 1 Iteration 2 Iteration 3 Iteration 4 Lec14.51 Lec14.52
14 oftware Pipelining Example efore: Unrolled 3 times 1 L F0,0(R1) 2 A F4,F0,F2 3 0(R1),F4 4 L F6,-8(R1) 5 A F8,F6,F2 6-8(R1),F8 7 L F10,-16(R1) 8 A F12,F10,F2 9-16(R1),F12 10 UI R1,R1,#24 11 NEZ R1,LOOP ymbolic Loop Unrolling aximize result-use distance Less code space than unrolling Fill & drain pipe only once per loop After: oftware Pipelined 1 0(R1),F4 ; tores [i] 2 A F4,F0,F2 ; Adds to [i-1] 3 L F0,-16(R1); Loads [i-2] 4 UI R1,R1,#8 5 NEZ R1,LOOP W Pipeline Time Loop Unrolled Time vs. once per each unrolled iteration in loop unrolling overlapped ops Lec14.53 oftware Pipelining with Loop Unrolling in VLIW ory ory FP FP Int. op/ Clock reference 1 reference 2 operation 1 op. 2 branch L F0,-48(R1) T 0(R1),F4 A F4,F0,F2 1 L F6,-56(R1) T -8(R1),F8 A F8,F6,F2 UI R1,R1,#24 2 L F10,-40(R1) T 8(R1),F12 A F12,F10,F2 NEZ R1,LOOP 3 oftware pipelined across 9 iterations of original loop In each iteration of above loop, we: - tore to m,m-8,m-16 (iterations I-3,I-2,I-1) - Compute for m-24,m-32,m-40 (iterations I,I+1,I+2) - Load from m-48,m-56,m-64 (iterations I+3,I+4,I+ 9 results in 9 cycles, or 1 clock per iteration Average: 3.3 ops per clock, 66% efficiency Note: Need less registers for software pipelining (only using 7 registers here, was using 1 Lec14.54 Trace cheduling Parallelism across IF branches vs. LOOP branches Two steps: Trace election - Find likely sequence of basic blocks (trace) of (statically predicted or profile predicted) long sequence of straight-line code Trace Compaction - queeze trace into few VLIW instructions - Need bookkeeping code in case prediction is wrong Compiler undoes bad guess (discards values in registers) ubtle compiler bugs mean wrong answer vs. pooer performance; no hardware interlocks ummary Hazards limit performance tructural: need more HW resources ata: need foarding, compiler scheduling Control: early evaluation &, delayed branch, prediction ata hazards must be handled carefully: RAW data hazards handled by foarding WAW and WAR hazards don t exist in 5-stage pipeline IP I instruction set architecture made pipeline visible (delayed branch, delayed load) Exceptions in 5-stage pipeline recorded when they occur, but acted on only at (end of E) stage ust flush all previous instructions ore performance from deeper pipelines, parallelism Lec14.55 Lec14.56
Recap: Summary of Pipelining Basics
Recap: ummary of Pipelining asics C152 Computer rchitecture and Engineering Lecture 14 Pipelining Control Continued Introduction to dvanced Pipelining arch 8, 2001 John Kubiatowicz (http.cs.berkeley.edu/~kubitron)
More informationReview: Pipelining. Key to pipelining: smooth flow Making all instructions the same length can increase performance!
Review: Pipelining CS152 Computer Architecture and Engineering Lecture 15 Advanced pipelining/compiler Scheduling October 24, 2001 John Kubiatowicz (http.cs.berkeley.edu/~kubitron) lecture slides: http://www-inst.eecs.berkeley.edu/~cs152/
More informationT a s k B C D. O r d e r
an Jose tate University EE176 - Fall 1998 Computer rchitecture and Engineering Lecture 12: Introduction to Pipelining (Part II) Instructor: Christopher H. Pham http://www.engr.sjsu.edu/~cpham/ T a s k
More informationLecture 9: Case Study MIPS R4000 and Introduction to Advanced Pipelining Professor Randy H. Katz Computer Science 252 Spring 1996
Lecture 9: Case Study MIPS R4000 and Introduction to Advanced Pipelining Professor Randy H. Katz Computer Science 252 Spring 1996 RHK.SP96 1 Review: Evaluating Branch Alternatives Two part solution: Determine
More informationLecture 6 MIPS R4000 and Instruction Level Parallelism. Computer Architectures S
Lecture 6 MIPS R4000 and Instruction Level Parallelism Computer Architectures 521480S Case Study: MIPS R4000 (200 MHz, 64-bit instructions, MIPS-3 instruction set) 8 Stage Pipeline: first half of fetching
More informationCS152 Computer Architecture and Engineering Lecture 15
CS152 Computer Architecture and Engineering Lecture 15 Advanced pipelining/compiler Scheduling Dynamic Scheduling I March 13, 2001 John Kubiatowicz (http.cs.berkeley.edu/~kubitron) lecture slides: http://www-inst.eecs.berkeley.edu/~cs152/
More informationExploiting ILP with SW Approaches. Aleksandar Milenković, Electrical and Computer Engineering University of Alabama in Huntsville
Lecture : Exploiting ILP with SW Approaches Aleksandar Milenković, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Outline Basic Pipeline Scheduling and Loop
More informationReview: Evaluating Branch Alternatives. Lecture 3: Introduction to Advanced Pipelining. Review: Evaluating Branch Prediction
Review: Evaluating Branch Alternatives Lecture 3: Introduction to Advanced Pipelining Two part solution: Determine branch taken or not sooner, AND Compute taken branch address earlier Pipeline speedup
More informationMulti-cycle Instructions in the Pipeline (Floating Point)
Lecture 6 Multi-cycle Instructions in the Pipeline (Floating Point) Introduction to instruction level parallelism Recap: Support of multi-cycle instructions in a pipeline (App A.5) Recap: Superpipelining
More informationLecture 8 Dynamic Branch Prediction, Superscalar and VLIW. Computer Architectures S
Lecture 8 Dynamic Branch Prediction, Superscalar and VLIW Computer Architectures 521480S Dynamic Branch Prediction Performance = ƒ(accuracy, cost of misprediction) Branch History Table (BHT) is simplest
More informationCISC 662 Graduate Computer Architecture Lecture 13 - CPI < 1
CISC 662 Graduate Computer Architecture Lecture 13 - CPI < 1 Michela Taufer http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from John Hennessy and David Patterson s: Computer
More informationCS252 Graduate Computer Architecture Lecture 5. Interrupt Controller CPU. Interrupts, Software Scheduling around Hazards February 1 st, 2012
CS252 Graduate Computer Architecture Lecture 5 Interrupts, Software Scheduling around Hazards February 1 st, 2012 John Kubiatowicz Electrical Engineering and Computer Sciences University of California,
More informationFour Steps of Speculative Tomasulo cycle 0
HW support for More ILP Hardware Speculative Execution Speculation: allow an instruction to issue that is dependent on branch, without any consequences (including exceptions) if branch is predicted incorrectly
More informationארכי טק טורת יחיד ת עיבוד מרכזי ת
ארכי טק טורת יחיד ת עיבוד מרכזי ת (36113741) תשס"ג סמסטר א' March, 2007 Hugo Guterman (hugo@ee.bgu.ac.il) Web site: http://www.ee.bgu.ac.il/~cpuarch Arch. CPU L5 Pipeline II 1 Outline More pipelining Control
More information( ) תשס"ח סמסטר ב' May, 2008 Hugo Guterman Web site:
ארכיטקטורת יחידת עיבוד מרכזית (36113741) תשס"ח סמסטר ב' May, 2008 Hugo Guterman (hugo@ee.bgu.ac.il) Web site: http://www.ee.bgu.ac.il/~cpuarch Arch. CPU L5 Pipeline II 1 Outline More pipelining Control
More informationCS425 Computer Systems Architecture
CS425 Computer Systems Architecture Fall 2018 Static Instruction Scheduling 1 Techniques to reduce stalls CPI = Ideal CPI + Structural stalls per instruction + RAW stalls per instruction + WAR stalls per
More informationCOSC4201. Prof. Mokhtar Aboelaze York University
COSC4201 Chapter 3 Multi Cycle Operations Prof. Mokhtar Aboelaze York University Based on Slides by Prof. L. Bhuyan (UCR) Prof. M. Shaaban (RTI) 1 Multicycle Operations More than one function unit, each
More informationPage 1. CISC 662 Graduate Computer Architecture. Lecture 8 - ILP 1. Pipeline CPI. Pipeline CPI (I) Pipeline CPI (II) Michela Taufer
CISC 662 Graduate Computer Architecture Lecture 8 - ILP 1 Michela Taufer Pipeline CPI http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from John Hennessy and David Patterson
More informationLecture 4: Introduction to Advanced Pipelining
Lecture 4: Introduction to Advanced Pipelining Prepared by: Professor David A. Patterson Computer Science 252, Fall 1996 Edited and presented by : Prof. Kurt Keutzer Computer Science 252, Spring 2000 KK
More informationExecution/Effective address
Pipelined RC 69 Pipelined RC Instruction Fetch IR mem[pc] NPC PC+4 Instruction Decode/Operands fetch A Regs[rs]; B regs[rt]; Imm sign extended immediate field Execution/Effective address Memory Ref ALUOutput
More informationInstruction Level Parallelism. Appendix C and Chapter 3, HP5e
Instruction Level Parallelism Appendix C and Chapter 3, HP5e Outline Pipelining, Hazards Branch prediction Static and Dynamic Scheduling Speculation Compiler techniques, VLIW Limits of ILP. Implementation
More informationPredict Not Taken. Revisiting Branch Hazard Solutions. Filling the delay slot (e.g., in the compiler) Delayed Branch
branch taken Revisiting Branch Hazard Solutions Stall Predict Not Taken Predict Taken Branch Delay Slot Branch I+1 I+2 I+3 Predict Not Taken branch not taken Branch I+1 IF (bubble) (bubble) (bubble) (bubble)
More informationOutline Review: Basic Pipeline Scheduling and Loop Unrolling Multiple Issue: Superscalar, VLIW. CPE 631 Session 19 Exploiting ILP with SW Approaches
Session xploiting ILP with SW Approaches lectrical and Computer ngineering University of Alabama in Huntsville Outline Review: Basic Pipeline Scheduling and Loop Unrolling Multiple Issue: Superscalar,
More informationPage # CISC 662 Graduate Computer Architecture. Lecture 8 - ILP 1. Pipeline CPI. Pipeline CPI (I) Michela Taufer
CISC 662 Graduate Computer Architecture Lecture 8 - ILP 1 Michela Taufer http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from John Hennessy and David Patterson s: Computer Architecture,
More informationComputer Science 246 Computer Architecture
Computer Architecture Spring 2009 Harvard University Instructor: Prof. dbrooks@eecs.harvard.edu Compiler ILP Static ILP Overview Have discussed methods to extract ILP from hardware Why can t some of these
More informationSuper Scalar. Kalyan Basu March 21,
Super Scalar Kalyan Basu basu@cse.uta.edu March 21, 2007 1 Super scalar Pipelines A pipeline that can complete more than 1 instruction per cycle is called a super scalar pipeline. We know how to build
More informationInstruction Pipelining Review
Instruction Pipelining Review Instruction pipelining is CPU implementation technique where multiple operations on a number of instructions are overlapped. An instruction execution pipeline involves a number
More informationAdvanced issues in pipelining
Advanced issues in pipelining 1 Outline Handling exceptions Supporting multi-cycle operations Pipeline evolution Examples of real pipelines 2 Handling exceptions 3 Exceptions In pipelined execution, one
More informationEITF20: Computer Architecture Part2.2.1: Pipeline-1
EITF20: Computer Architecture Part2.2.1: Pipeline-1 Liang Liu liang.liu@eit.lth.se 1 Outline Reiteration Pipelining Harzards Structural hazards Data hazards Control hazards Implementation issues Multi-cycle
More informationReview: Compiler techniques for parallelism Loop unrolling Ÿ Multiple iterations of loop in software:
CS152 Computer Architecture and Engineering Lecture 17 Dynamic Scheduling: Tomasulo March 20, 2001 John Kubiatowicz (http.cs.berkeley.edu/~kubitron) lecture slides: http://www-inst.eecs.berkeley.edu/~cs152/
More informationCS425 Computer Systems Architecture
CS425 Computer Systems Architecture Fall 2017 Multiple Issue: Superscalar and VLIW CS425 - Vassilis Papaefstathiou 1 Example: Dynamic Scheduling in PowerPC 604 and Pentium Pro In-order Issue, Out-of-order
More informationInstruction Level Parallelism. ILP, Loop level Parallelism Dependences, Hazards Speculation, Branch prediction
Instruction Level Parallelism ILP, Loop level Parallelism Dependences, Hazards Speculation, Branch prediction Basic Block A straight line code sequence with no branches in except to the entry and no branches
More informationPage 1. Recall from Pipelining Review. Lecture 15: Instruction Level Parallelism and Dynamic Execution
CS252 Graduate Computer Architecture Recall from Pipelining Review Lecture 15: Instruction Level Parallelism and Dynamic Execution March 11, 2002 Prof. David E. Culler Computer Science 252 Spring 2002
More informationCSE 820 Graduate Computer Architecture. week 6 Instruction Level Parallelism. Review from Last Time #1
CSE 820 Graduate Computer Architecture week 6 Instruction Level Parallelism Based on slides by David Patterson Review from Last Time #1 Leverage Implicit Parallelism for Performance: Instruction Level
More informationPage 1. Recall from Pipelining Review. Lecture 16: Instruction Level Parallelism and Dynamic Execution #1: Ideas to Reduce Stalls
CS252 Graduate Computer Architecture Recall from Pipelining Review Lecture 16: Instruction Level Parallelism and Dynamic Execution #1: March 16, 2001 Prof. David A. Patterson Computer Science 252 Spring
More informationNOW Handout Page 1. Review from Last Time #1. CSE 820 Graduate Computer Architecture. Lec 8 Instruction Level Parallelism. Outline
CSE 820 Graduate Computer Architecture Lec 8 Instruction Level Parallelism Based on slides by David Patterson Review Last Time #1 Leverage Implicit Parallelism for Performance: Instruction Level Parallelism
More informationCMSC 411 Computer Systems Architecture Lecture 6 Basic Pipelining 3. Complications With Long Instructions
CMSC 411 Computer Systems Architecture Lecture 6 Basic Pipelining 3 Long Instructions & MIPS Case Study Complications With Long Instructions So far, all MIPS instructions take 5 cycles But haven't talked
More informationDynamic Control Hazard Avoidance
Dynamic Control Hazard Avoidance Consider Effects of Increasing the ILP Control dependencies rapidly become the limiting factor they tend to not get optimized by the compiler more instructions/sec ==>
More informationECE473 Computer Architecture and Organization. Pipeline: Control Hazard
Computer Architecture and Organization Pipeline: Control Hazard Lecturer: Prof. Yifeng Zhu Fall, 2015 Portions of these slides are derived from: Dave Patterson UCB Lec 15.1 Pipelining Outline Introduction
More informationEITF20: Computer Architecture Part2.2.1: Pipeline-1
EITF20: Computer Architecture Part2.2.1: Pipeline-1 Liang Liu liang.liu@eit.lth.se 1 Outline Reiteration Pipelining Harzards Structural hazards Data hazards Control hazards Implementation issues Multi-cycle
More informationEITF20: Computer Architecture Part2.2.1: Pipeline-1
EITF20: Computer Architecture Part2.2.1: Pipeline-1 Liang Liu liang.liu@eit.lth.se 1 Outline Reiteration Pipelining Harzards Structural hazards Data hazards Control hazards Implementation issues Multi-cycle
More informationInstruction Level Parallelism
Instruction Level Parallelism The potential overlap among instruction execution is called Instruction Level Parallelism (ILP) since instructions can be executed in parallel. There are mainly two approaches
More informationPipelining and Exploiting Instruction-Level Parallelism (ILP)
Pipelining and Exploiting Instruction-Level Parallelism (ILP) Pipelining and Instruction-Level Parallelism (ILP). Definition of basic instruction block Increasing Instruction-Level Parallelism (ILP) &
More informationEE 4683/5683: COMPUTER ARCHITECTURE
EE 4683/5683: COMPUTER ARCHITECTURE Lecture 4A: Instruction Level Parallelism - Static Scheduling Avinash Kodi, kodi@ohio.edu Agenda 2 Dependences RAW, WAR, WAW Static Scheduling Loop-carried Dependence
More informationComplications with long instructions. CMSC 411 Computer Systems Architecture Lecture 6 Basic Pipelining 3. How slow is slow?
Complications with long instructions CMSC 411 Computer Systems Architecture Lecture 6 Basic Pipelining 3 Long Instructions & MIPS Case Study So far, all MIPS instructions take 5 cycles But haven't talked
More informationMinimizing Data hazard Stalls by Forwarding Data Hazard Classification Data Hazards Present in Current MIPS Pipeline
Instruction Pipelining Review: MIPS In-Order Single-Issue Integer Pipeline Performance of Pipelines with Stalls Pipeline Hazards Structural hazards Data hazards Minimizing Data hazard Stalls by Forwarding
More informationRecall from Pipelining Review. Lecture 16: Instruction Level Parallelism and Dynamic Execution #1: Ideas to Reduce Stalls
CS252 Graduate Computer Architecture Recall from Pipelining Review Lecture 16: Instruction Level Parallelism and Dynamic Execution #1: March 16, 2001 Prof. David A. Patterson Computer Science 252 Spring
More informationAdministrivia. CMSC 411 Computer Systems Architecture Lecture 14 Instruction Level Parallelism (cont.) Control Dependencies
Administrivia CMSC 411 Computer Systems Architecture Lecture 14 Instruction Level Parallelism (cont.) HW #3, on memory hierarchy, due Tuesday Continue reading Chapter 3 of H&P Alan Sussman als@cs.umd.edu
More informationCS 152 Computer Architecture and Engineering
CS 152 Computer Architecture and Engineering Lecture 18 Advanced Processors II 2006-10-31 John Lazzaro (www.cs.berkeley.edu/~lazzaro) Thanks to Krste Asanovic... TAs: Udam Saini and Jue Sun www-inst.eecs.berkeley.edu/~cs152/
More informationCS61C : Machine Structures
inst.eecs.berkeley.edu/~cs61c/su05 CS61C : Machine Structures Lecture #19: Pipelining II 2005-07-21 Andy Carle CS 61C L19 Pipelining II (1) Review: Datapath for MIPS PC instruction memory rd rs rt registers
More informationLoad1 no Load2 no Add1 Y Sub Reg[F2] Reg[F6] Add2 Y Add Reg[F2] Add1 Add3 no Mult1 Y Mul Reg[F2] Reg[F4] Mult2 Y Div Reg[F6] Mult1
Instruction Issue Execute Write result L.D F6, 34(R2) L.D F2, 45(R3) MUL.D F0, F2, F4 SUB.D F8, F2, F6 DIV.D F10, F0, F6 ADD.D F6, F8, F2 Name Busy Op Vj Vk Qj Qk A Load1 no Load2 no Add1 Y Sub Reg[F2]
More informationCMSC 611: Advanced Computer Architecture
CMSC 611: Advanced Computer Architecture Instruction Level Parallelism Some material adapted from Mohamed Younis, UMBC CMSC 611 Spr 2003 course slides Some material adapted from Hennessy & Patterson /
More informationBasic Pipelining Concepts
Basic ipelining oncepts Appendix A (recommended reading, not everything will be covered today) Basic pipelining ipeline hazards Data hazards ontrol hazards Structural hazards Multicycle operations Execution
More informationELEC 5200/6200 Computer Architecture and Design Fall 2016 Lecture 9: Instruction Level Parallelism
ELEC 5200/6200 Computer Architecture and Design Fall 2016 Lecture 9: Instruction Level Parallelism Ujjwal Guin, Assistant Professor Department of Electrical and Computer Engineering Auburn University,
More informationCOMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. 5 th. Edition. Chapter 4. The Processor
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface 5 th Edition Chapter 4 The Processor Introduction CPU performance factors Instruction count Determined by ISA and compiler CPI and Cycle
More informationInstruction-Level Parallelism (ILP)
Instruction Level Parallelism Instruction-Level Parallelism (ILP): overlap the execution of instructions to improve performance 2 approaches to exploit ILP: 1. Rely on hardware to help discover and exploit
More informationLecture 7: Pipelining Contd. More pipelining complications: Interrupts and Exceptions
Lecture 7: Pipelining Contd. Kunle Olukotun Gates 302 kunle@ogun.stanford.edu http://www-leland.stanford.edu/class/ee282h/ 1 More pipelining complications: Interrupts and Exceptions Hard to handle in pipelined
More informationPipelining. Principles of pipelining. Simple pipelining. Structural Hazards. Data Hazards. Control Hazards. Interrupts. Multicycle operations
Principles of pipelining Pipelining Simple pipelining Structural Hazards Data Hazards Control Hazards Interrupts Multicycle operations Pipeline clocking ECE D52 Lecture Notes: Chapter 3 1 Sequential Execution
More informationData Hazards Compiler Scheduling Pipeline scheduling or instruction scheduling: Compiler generates code to eliminate hazard
Data Hazards Compiler Scheduling Pipeline scheduling or instruction scheduling: Compiler generates code to eliminate hazard Consider: a = b + c; d = e - f; Assume loads have a latency of one clock cycle:
More informationLecture 9. Pipeline Hazards. Christos Kozyrakis Stanford University
Lecture 9 Pipeline Hazards Christos Kozyrakis Stanford University http://eeclass.stanford.edu/ee18b 1 Announcements PA-1 is due today Electronic submission Lab2 is due on Tuesday 2/13 th Quiz1 grades will
More informationCPE 631 Lecture 09: Instruction Level Parallelism and Its Dynamic Exploitation
Lecture 09: Instruction Level Parallelism and Its Dynamic Exploitation Aleksandar Milenkovic, milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville Outline Instruction
More informationGetting CPI under 1: Outline
CMSC 411 Computer Systems Architecture Lecture 12 Instruction Level Parallelism 5 (Improving CPI) Getting CPI under 1: Outline More ILP VLIW branch target buffer return address predictor superscalar more
More informationEECC551 - Shaaban. 1 GHz? to???? GHz CPI > (?)
Evolution of Processor Performance So far we examined static & dynamic techniques to improve the performance of single-issue (scalar) pipelined CPU designs including: static & dynamic scheduling, static
More informationComputer Systems Architecture I. CSE 560M Lecture 5 Prof. Patrick Crowley
Computer Systems Architecture I CSE 560M Lecture 5 Prof. Patrick Crowley Plan for Today Note HW1 was assigned Monday Commentary was due today Questions Pipelining discussion II 2 Course Tip Question 1:
More informationCOMPUTER ORGANIZATION AND DESI
COMPUTER ORGANIZATION AND DESIGN 5 Edition th The Hardware/Software Interface Chapter 4 The Processor 4.1 Introduction Introduction CPU performance factors Instruction count Determined by ISA and compiler
More information5008: Computer Architecture
5008: Computer Architecture Chapter 2 Instruction-Level Parallelism and Its Exploitation CA Lecture05 - ILP (cwliu@twins.ee.nctu.edu.tw) 05-1 Review from Last Lecture Instruction Level Parallelism Leverage
More informationCS 61C: Great Ideas in Computer Architecture Pipelining and Hazards
CS 61C: Great Ideas in Computer Architecture Pipelining and Hazards Instructors: Vladimir Stojanovic and Nicholas Weaver http://inst.eecs.berkeley.edu/~cs61c/sp16 1 Pipelined Execution Representation Time
More informationCOMPUTER ORGANIZATION AND DESIGN
COMPUTER ORGANIZATION AND DESIGN 5 Edition th The Hardware/Software Interface Chapter 4 The Processor 4.1 Introduction Introduction CPU performance factors Instruction count CPI and Cycle time Determined
More informationMultiple Issue ILP Processors. Summary of discussions
Summary of discussions Multiple Issue ILP Processors ILP processors - VLIW/EPIC, Superscalar Superscalar has hardware logic for extracting parallelism - Solutions for stalls etc. must be provided in hardware
More informationHardware-based Speculation
Hardware-based Speculation Hardware-based Speculation To exploit instruction-level parallelism, maintaining control dependences becomes an increasing burden. For a processor executing multiple instructions
More informationFull Datapath. Chapter 4 The Processor 2
Pipelining Full Datapath Chapter 4 The Processor 2 Datapath With Control Chapter 4 The Processor 3 Performance Issues Longest delay determines clock period Critical path: load instruction Instruction memory
More informationEECC551 Exam Review 4 questions out of 6 questions
EECC551 Exam Review 4 questions out of 6 questions (Must answer first 2 questions and 2 from remaining 4) Instruction Dependencies and graphs In-order Floating Point/Multicycle Pipelining (quiz 2) Improving
More informationMetodologie di Progettazione Hardware-Software
Metodologie di Progettazione Hardware-Software Advanced Pipelining and Instruction-Level Paralelism Metodologie di Progettazione Hardware/Software LS Ing. Informatica 1 ILP Instruction-level Parallelism
More informationMIPS An ISA for Pipelining
Pipelining: Basic and Intermediate Concepts Slides by: Muhamed Mudawar CS 282 KAUST Spring 2010 Outline: MIPS An ISA for Pipelining 5 stage pipelining i Structural Hazards Data Hazards & Forwarding Branch
More informationLECTURE 3: THE PROCESSOR
LECTURE 3: THE PROCESSOR Abridged version of Patterson & Hennessy (2013):Ch.4 Introduction CPU performance factors Instruction count Determined by ISA and compiler CPI and Cycle time Determined by CPU
More informationMIPS Pipelining. Computer Organization Architectures for Embedded Computing. Wednesday 8 October 14
MIPS Pipelining Computer Organization Architectures for Embedded Computing Wednesday 8 October 14 Many slides adapted from: Computer Organization and Design, Patterson & Hennessy 4th Edition, 2011, MK
More informationAppendix C: Pipelining: Basic and Intermediate Concepts
Appendix C: Pipelining: Basic and Intermediate Concepts Key ideas and simple pipeline (Section C.1) Hazards (Sections C.2 and C.3) Structural hazards Data hazards Control hazards Exceptions (Section C.4)
More informationDepartment of Computer and IT Engineering University of Kurdistan. Computer Architecture Pipelining. By: Dr. Alireza Abdollahpouri
Department of Computer and IT Engineering University of Kurdistan Computer Architecture Pipelining By: Dr. Alireza Abdollahpouri Pipelined MIPS processor Any instruction set can be implemented in many
More informationCOSC 6385 Computer Architecture - Pipelining
COSC 6385 Computer Architecture - Pipelining Fall 2006 Some of the slides are based on a lecture by David Culler, Instruction Set Architecture Relevant features for distinguishing ISA s Internal storage
More informationUG4 Honours project selection: Talk to Vijay or Boris if interested in computer architecture projects
Announcements UG4 Honours project selection: Talk to Vijay or Boris if interested in computer architecture projects Inf3 Computer Architecture - 2017-2018 1 Last time: Tomasulo s Algorithm Inf3 Computer
More informationLecture 9: Multiple Issue (Superscalar and VLIW)
Lecture 9: Multiple Issue (Superscalar and VLIW) Iakovos Mavroidis Computer Science Department University of Crete Example: Dynamic Scheduling in PowerPC 604 and Pentium Pro In-order Issue, Out-of-order
More informationUNIVERSITY OF MASSACHUSETTS Dept. of Electrical & Computer Engineering. Computer Architecture ECE 568
UNIVERSITY OF MASSACHUSETTS Dept. of Electrical & Computer Engineering Computer Architecture ECE 568 Part 10 Compiler Techniques / VLIW Israel Koren ECE568/Koren Part.10.1 FP Loop Example Add a scalar
More informationLecture 5: VLIW, Software Pipelining, and Limits to ILP. Review: Tomasulo
Lecture 5: VLIW, Software Pipelining, and Limits to ILP Professor David A. Patterson Computer Science 252 Spring 1998 DAP.F96 1 Review: Tomasulo Prevents Register as bottleneck Avoids WAR, WAW hazards
More informationComputer Architecture
Lecture 3: Pipelining Iakovos Mavroidis Computer Science Department University of Crete 1 Previous Lecture Measurements and metrics : Performance, Cost, Dependability, Power Guidelines and principles in
More informationT = I x CPI x C. Both effective CPI and clock cycle C are heavily influenced by CPU design. CPI increased (3-5) bad Shorter cycle good
CPU performance equation: T = I x CPI x C Both effective CPI and clock cycle C are heavily influenced by CPU design. For single-cycle CPU: CPI = 1 good Long cycle time bad On the other hand, for multi-cycle
More informationCS 110 Computer Architecture. Pipelining. Guest Lecture: Shu Yin. School of Information Science and Technology SIST
CS 110 Computer Architecture Pipelining Guest Lecture: Shu Yin http://shtech.org/courses/ca/ School of Information Science and Technology SIST ShanghaiTech University Slides based on UC Berkley's CS61C
More informationChapter 4. The Processor
Chapter 4 The Processor Introduction CPU performance factors Instruction count Determined by ISA and compiler CPI and Cycle time Determined by CPU hardware We will examine two MIPS implementations A simplified
More informationCISC 662 Graduate Computer Architecture Lecture 7 - Multi-cycles
CISC 662 Graduate Computer Architecture Lecture 7 - Multi-cycles Michela Taufer http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from John Hennessy and David Patterson s: Computer
More informationCSE 533: Advanced Computer Architectures. Pipelining. Instructor: Gürhan Küçük. Yeditepe University
CSE 533: Advanced Computer Architectures Pipelining Instructor: Gürhan Küçük Yeditepe University Lecture notes based on notes by Mark D. Hill and John P. Shen Updated by Mikko Lipasti Pipelining Forecast
More informationLecture 7 Pipelining. Peng Liu.
Lecture 7 Pipelining Peng Liu liupeng@zju.edu.cn 1 Review: The Single Cycle Processor 2 Review: Given Datapath,RTL -> Control Instruction Inst Memory Adr Op Fun Rt
More informationPipelining. Maurizio Palesi
* Pipelining * Adapted from David A. Patterson s CS252 lecture slides, http://www.cs.berkeley/~pattrsn/252s98/index.html Copyright 1998 UCB 1 References John L. Hennessy and David A. Patterson, Computer
More informationChapter 4. The Processor
Chapter 4 The Processor Introduction CPU performance factors Instruction count Determined by ISA and compiler CPI and Cycle time Determined by CPU hardware We will examine two MIPS implementations A simplified
More informationThomas Polzer Institut für Technische Informatik
Thomas Polzer tpolzer@ecs.tuwien.ac.at Institut für Technische Informatik Pipelined laundry: overlapping execution Parallelism improves performance Four loads: Speedup = 8/3.5 = 2.3 Non-stop: Speedup =
More informationCompiler Optimizations. Lecture 7 Overview of Superscalar Techniques. Memory Allocation by Compilers. Compiler Structure. Register allocation
Lecture 7 Overview of Superscalar Techniques CprE 581 Computer Systems Architecture, Fall 2013 Reading: Textbook, Ch. 3 Complexity-Effective Superscalar Processors, PhD Thesis by Subbarao Palacharla, Ch.1
More informationHandout 2 ILP: Part B
Handout 2 ILP: Part B Review from Last Time #1 Leverage Implicit Parallelism for Performance: Instruction Level Parallelism Loop unrolling by compiler to increase ILP Branch prediction to increase ILP
More informationPipelining. Ideal speedup is number of stages in the pipeline. Do we achieve this? 2. Improve performance by increasing instruction throughput ...
CHAPTER 6 1 Pipelining Instruction class Instruction memory ister read ALU Data memory ister write Total (in ps) Load word 200 100 200 200 100 800 Store word 200 100 200 200 700 R-format 200 100 200 100
More informationSome material adapted from Mohamed Younis, UMBC CMSC 611 Spr 2003 course slides Some material adapted from Hennessy & Patterson / 2003 Elsevier
Some material adapted from Mohamed Younis, UMBC CMSC 611 Spr 2003 course slides Some material adapted from Hennessy & Patterson / 2003 Elsevier Science Cases that affect instruction execution semantics
More informationCISC 662 Graduate Computer Architecture Lecture 7 - Multi-cycles. Interrupts and Exceptions. Device Interrupt (Say, arrival of network message)
CISC 662 Graduate Computer Architecture Lecture 7 - Multi-cycles Michela Taufer Interrupts and Exceptions http://www.cis.udel.edu/~taufer/teaching/cis662f07 Powerpoint Lecture Notes from John Hennessy
More informationComputer Science 146. Computer Architecture
Computer rchitecture Spring 2004 Harvard University Instructor: Prof. dbrooks@eecs.harvard.edu Lecture 11: Software Pipelining and Global Scheduling Lecture Outline Review of Loop Unrolling Software Pipelining
More informationCMCS Mohamed Younis CMCS 611, Advanced Computer Architecture 1
CMCS 611-101 Advanced Computer Architecture Lecture 9 Pipeline Implementation Challenges October 5, 2009 www.csee.umbc.edu/~younis/cmsc611/cmsc611.htm Mohamed Younis CMCS 611, Advanced Computer Architecture
More information