1. Datorteknik F1 bild 1 Instruction Level Parallelism Scalar-processors –the model so far SuperScalar –multiple execution units in parallel VLIW –multiple instructions read in parallel

2. Datorteknik F1 bild 2 Scalar Processors T = Nq * CPI * Ct –The time to perform a task –Nq, number of instruction, CPI cycles/instruction, Ct cycle- time Pipeline –CPI = 1 –Ct determined by critical path But: –Floating point operations slow in software –Even in hardware (FPU) takes several cycles WHY NOT USE SEVERAL FLOATING POINT UNITS?

3. Datorteknik F1 bild 3 SuperScalar Processors IFDE ALU PFU 1 …. PFU n DMWB 1-cycle m-cycles Each unit may take several cycles for finish issuecompletion

4. Datorteknik F1 bild 4 Instruction VS Machine Parallelism Instruction Parallelism –Average nr of instructions that can be executed in parallel –Depends on; “true dependencies” Branches in relation to other instructions Machine Parallelism –The ability of the hardware to utilize instruction parallelism –Depends on; Nr of instructions that can be fetched and executed each cycle instruction memory bandwidth and instruction buffer (window) available resources The ability to spot instruction parallelism

5. Datorteknik F1 bild 5 Example 1 1) add $t0 $t1 $t2 2) addi $t0 $t0 1 3) sub $t3 $t1 $t2 4) subi $t3 $t3 1 1) add $t0 $t1 $t2 2) addi $t0 $t0 1 3) sub $t3 $t1 $t2 4) subi $t3 $t3 1 Concurrently executed instruction lookahead or “prefetch” dependent independent

6. Datorteknik F1 bild 6 Issue & Completion Out of order issue, (starts “out of order”) –RAW hazards –WAR hazard (write after read) Out of order completion, (finishes “out of order”) –WAW, Antidependence hazard (result overwritten) Issue 1) add $t0 $t1 $t2 2) addi $t0 $t0 1 3) sub $t3 $t1 $t2 4) subi $t3 $t3 1 1)3) 2)4) Completion 1)3) 2)4) - - -- - - 2-parallel execution units 4-stage pipeline

7. Datorteknik F1 bild 7 Tomasulo’s Algorithm IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6... AIDLE B C...

8. Datorteknik F1 bild 8 Instruction Issue IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6 2 3 mul $r1 2 3 A... $r1ABUSY BIDLE C...

9. Datorteknik F1 bild 9 Instruction Issue IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6 2 3 A 4 mul $r1 2 3 mul $r2 A 4 A$r1 B$r2... ABUSY BWAIT CIDLE...

10. Datorteknik F1 bild 10 Instruction Issue IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6 2 3 A 4 ABUSY BWAIT CBUSY mul $r1 2 3 mul $r2 A 4 A$r1 C$r2... mul $r2 5 6 Reg $r2 gets newer value

11. Datorteknik F1 bild 11 Clock until A and B finish IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6 2 3 6 4 AIDLE BBUSY CIDLE mul $r1 2 3 mul $r2 6 4 6$r1 30$r2... mul $r2 5 6

12. Datorteknik F1 bild 12 Clock until B finishes IFDE A BDMWB C mul $r1 2 3 mul $r2 $r1 4 mul $r2 5 6 2 3 6 2 AIDLE B C mul $r2 6 4 6$r1 30$r2... NOT CHANGED!

13. Datorteknik F1 bild 13 SuperScalar Designs 3-8 times faster than Scalar designs depending on –Instruction parallelism (upper bound) –Machine parallelism Pros –Backward compatible (optimization is done at run time) Cons –Complex hardware implementation –Not scaleable (Instruction Parallelism)

14. Datorteknik F1 bild 14 VLIW Why not let the compiler do the work? Use a Very Long Instruction Word (VLIW) –Consisting of many instructions is parallel –Each time we read one VLIW instruction we actually issue all instructions contained in the VLIW instruction

15. Datorteknik F1 bild 15 VLIW IFDEEXDMWB IFDEEXDMWB IFDEEXDMWB IFDEEXDMWB 32 128 VLIW instruction Usually the bottleneck

16. Datorteknik F1 bild 16 VLIW Let the compiler can do the instruction issuing –Let it take it’s time we do this only once, ADVANCED What if we change the architecture –Recompile the code –Could be done the first time you load a program Only recompiled when architecture changed We could also let the compiler know about –Cache configuration Nr levels, line size, nr lines, replacement strategy, writeback/writethrough etc. Hot Research Area!

17. Datorteknik F1 bild 17 VLIW Pros –We get high bandwidth to instruction memory –Cheap compared to SuperScalar Not much extra hardware needed –More parallelism We spot parallelism at a higher level (C, MODULA, JAVA?) We can use advanced algorithms for optimization –New architectures can be utilized by recompilation Cons –Software compatibility –It has not “HIT THE MARKET” (yet).

18. Datorteknik F1 bild 18 4 State Branch Prediction loop : A bne 100times loop B j loop BRA NO BRA BRA NO BRA BRA NO BRA We always predict BRA (1) in the inner loop, when exit we fail once and go to (2). Next time we still predict BRA (2) and go to (1) 12 NO BRA Predict Branch Predict no branch BRA

19. Datorteknik F1 bild 19 Branch Prediction The 4-states are stored in 2 bits in the instruction cache together with the conditional Branch instruction We predict the branch –We prefetch the predicted instructions –We issue these before we know if branch taken! When predicting fails we abort issued instructions

20. Datorteknik F1 bild 20 Branch Prediction loop bne $r1 looppredict branch taken 1) 2) 3) Instructions 1) 2) and 3) are prefetched and may already be issued when we know the value of $r1, since $r1 might be waiting for some unit to finish In case of prediction failure we have to abort the issued instructions and start fetching 4) 5) and 6)

21. Datorteknik F1 bild 21 Multiple Branch Targets loop bne $r1 loop 1) 2) 3) Instructions 1) 2) 3) 4) 5) and 6) is prefetched and may already be issued when we know the value of $r1, since $r1 might be waiting for some unit to finish As soon as we know $r1 we abort the redundant instructions. VERY COMPLEX!!!