Lecture 12: Spiral: Domain Specific HLS. James C. Hoe Department of ECE Carnegie Mellon University
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1 8 643 Lecture : Spiral: Domai Specific HLS James C. Hoe Departmet of ECE Caregie Mello Uiversity F7 L S, James C. Hoe, CMU/ECE/CALCM, 07
2 Houseeepig Your goal today: see a eample of really highlevel sythesis (this lecture ot o Midterm) Notices Hadout #4: lab, due oo, 0/6 Hadout #5: lab 3, due oo, 0/0.5 wees to project proposal.5 wee to midterm Readigs sim Milder, et al., Computer Geeratio of Hardware for Liear Digital Sigal Processig Trasforms, TODAES, April F7 L S, James C. Hoe, CMU/ECE/CALCM, 07
3 Coflict btw High Level ad Geerality F7 L S3, James C. Hoe, CMU/ECE/CALCM, 07 high level: tool ows better tha you HLS: tool decides what you ca say ad what you mea RTL sythesis: geeral purpose but special hadlig of structures lie FSM, arith, etc. place ad route: wors the same o matter what desig
4 Spiral DFTge: how high ca you go? F7 L S4, James C. Hoe, CMU/ECE/CALCM, 07
5 Desig Space ad Quality of Result 49 slices 3 throughput F7 L S5, James C. Hoe, CMU/ECE/CALCM, 07 [Milder, et al., 0]
6 SPIRAL Framewor I wat a DFT of size 04 SPIRAL automatio starts here where most tools begi automatig the problem F7 L S6, James C. Hoe, CMU/ECE/CALCM, 07 Priciple : Domai owledge i the system Priciple : Optimizatio at a high level of abstractio
7 Very High Level Descriptio F7 L S7, James C. Hoe, CMU/ECE/CALCM, 07
8 Liear Trasforms Liear trasform is a matri vector multiplicatio computig by defiitio taes O(N ) operatios the matri has structure E.g. discrete Fourier trasform: y = DFT N y 0 y. y j.. y N- = j 0.. N- e 0.. N- i j N N- i e -i/ F7 L S8, James C. Hoe, CMU/ECE/CALCM, 07 e.g., 8 th roots of uit
9 8 643 F7 L S9, James C. Hoe, CMU/ECE/CALCM, 07 Fast Algorithms Fast algorithm factors the matri ito a sequece of structured, sparse matrices cheaper sparse multiplies O(N log(n)) operatios E.g. Cooley Tuey Factorizatio of DFT 4 Matri formula represetatio i i i i i L DFT I D I DFT DFT
10 E.g. Cooley Tuey DFT m DFT is Factorizatio Rules m m DFT I D I DFT L D is a diagoal matri of twiddle factors L is a stride permutatio matri AB=[a j, B] is the tesor (or roecer) product m m e.g., I B B BB 0 A I a 0,0a0,0a0,0 0 a 0 0,0a,0a,0 0 a 0, a0,a0, 0 0 a, a 0 0,a, 0 B F7 L S0, James C. Hoe, CMU/ECE/CALCM, 07
11 Fast Fourier Trasform Algorithms Recursively factorize by Cooley Tuey rule util oly leaf cases remai (e.g. DFT r for radi r) DFT DFT I4 D I DFT4 L 8 4 DFT I D I DFT I D I DFT Epoetial umber of alteratives Each ruletree correspods a differet algorithm All cost O(N log(n)) F7 L S, James C. Hoe, CMU/ECE/CALCM, 07 4 DFT 8 DFT 4 DFT DFT DFT 4 8 L L DFT 8 DFT DFT 4 DFT DFT
12 Describig a Desig Space vs a Poit ( ) DCT II diag, / F ( II ) DCT P / / / DCT DCT DFT DFT F F ( IV ) ( IV F7 L S, James C. Hoe, CMU/ECE/CALCM, 07 S ( II ) ( IV ) DCT DCT I F Q DCT ( II ) D ) M M r ( I ) ( I ) B ( DCT DST ) C ( h) ( I / d I d ) ( I / d Fd ( h)) ( h) Circ ( h ) E DWT m DFT I D I DFT P / m / ( W ) ( DWT / ( W ) I / ) P ( I / W ) E K i i ik t WHT ( I WHT I ) i m Doe oce per trasform by a epert ad the tool becomes the epert
13 8 643 F7 L S3, James C. Hoe, CMU/ECE/CALCM, 07 Very High Level Sythesis
14 Formula to HW Give where is: apply, the apply, times i parallel is a permutatio permute is a diagoal scale B A A A F7 L S4, James C. Hoe, CMU/ECE/CALCM, 07
15 DFT 8 Eample DFT 8 4 DFT I D I DFT I D I DFT 4 8 L 8 4 L F7 L S5, James C. Hoe, CMU/ECE/CALCM, 07 (formula is applied from right to left)
16 Pease DFT 8 Eample stage stage stage F7 L S6, James C. Hoe, CMU/ECE/CALCM, 07
17 How about good HW? Formulas map aturally to combiatioal dataflow, but this is either good or realistic What if I wat DFT 6K? Sequetial datapath to reuse available HW idetify repeated erels istatiate erels uder resource costraits schedule computatio to reuse istatiated erels Do this at formula level with math level owledge F7 L S7, James C. Hoe, CMU/ECE/CALCM, 07
18 Tesor as Streamig Pipelie fully parallel F7 L S8, James C. Hoe, CMU/ECE/CALCM, 07 fully streamed partially streamed Lie data parallel loops we see i regular HLS
19 Pease DFT 8 stage stage stage F7 L S9, James C. Hoe, CMU/ECE/CALCM, 07
20 Streamig Pease DFT 8 f(l 8 4) ) f(l 8 4) ) f(l 8 4) ) f(r f(l 8 ) ) f(l 8 4) ) f(l 8 4) ) f(l 8 4) ) f(r f(l 8 ) ) stage stage stage F7 L S0, James C. Hoe, CMU/ECE/CALCM, 07
21 Iterative Reuse hr hr o reuse F7 L S, James C. Hoe, CMU/ECE/CALCM, 07 iteratively reuse partially iterative reuse Lie data depedet loops we see i regular HLS
22 Iterative Pease DFT 8,4,..., cost ; latecy Fie-graied cotrol over cost/latecy tradeoff F7 L S, James C. Hoe, CMU/ECE/CALCM, 07
23 Rewrite Rules for Streamig ad Reuse pragmas F7 L S3, James C. Hoe, CMU/ECE/CALCM, 07
24 8 643 F7 L S4, James C. Hoe, CMU/ECE/CALCM, 07 Applicability to other trasforms DFT radi DFT radi r D DFT WHT DCT (type II) H i i P L L L A DP 0 0 i DFT I L 0 i i L DFT I T R / 0 r i i r r r L DFT I T R / 0 r i r r r L WHT I
25 Toward Very High Level IPs F7 L S5, James C. Hoe, CMU/ECE/CALCM, 07
26 Is DFTge Easy to Use? F7 L S6, James C. Hoe, CMU/ECE/CALCM, 07
27 Easy to Use for Whom? Powerful? Very! Easy to use? Not Really.... low level cryptic domai specific parameters compleity of itegratig, usig, tuig ad validatig a istatiated IP withi a eclosig cotet If you wet to DFTge right ow which cofiguratio would you as for first? if ot good eough, how to get a better oe..... do you ow what good eough is F7 L S7, James C. Hoe, CMU/ECE/CALCM, 07
28 IP Authors IP Users Differet Kids of Eperts Applicatio Developers Assemble, cofigure ad itegrate multiple IPs to build larger chips Domai Eperts Kow the uderlyig algorithms ad theory specific to the domai Hardware Eperts Ca build HW based o a set of specs or SW implemetatio F7 L S8, James C. Hoe, CMU/ECE/CALCM, 07
29 Mae geerator the IP Why limit to structural view of desig Why ot offer also.... pre owledge about outcome & tradeoff of parameter combiatios IP specific meaigful parameterizatios, that is, as how fast? istead of how may? performace self moitor, iterface protocol checer ay X where IP authors ca do better tha IP users Shift burdes from IP users to IP authors mae owledge ad epertise reusable F7 L S9, James C. Hoe, CMU/ECE/CALCM, 07
30 Partig Thoughts Ecapsulatig domai owledge i a domai specific tool for truly high level desig automatio Why is Spiral DSP so good? As: it oly does liear DSP trasforms (fortuately FFT is pretty importat) very well uderstood mathematics highly structured, highly regular computatio eumerable desig space Uderlyig approach/framewor is geeralizable!! F7 L S30, James C. Hoe, CMU/ECE/CALCM, 07
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