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Published on June 17, 2007

Author: Barbara


Functional Design Using Behavioural and Structural Components:  Functional Design Using Behavioural and Structural Components Richard Sharp University of Cambridge aims ofthis research:  aims of this research SAFL is a Behavioural HDL Supports a functional programming style Designed for source-level program transformation Ease of analysis and optimisation Combine behaviour and structure? Verilog/VHDL do this to great effect… but as a result are very complex =andgt; transformation VERY difficult. talkoverview:  talk overview Behavioural HDL: SAFL Structural HDL: Magma Integrating SAFL + Magma Case Study Conclusions and further work SAFL:a behavioural HDL:  SAFL: a behavioural HDL Functional Call-by-value First-order statically allocated functional language General properties Hardware-specific properties a SAFLexample:  a SAFL example mult f cube circuit structure: Behavioural, … but … captures system-level structure One 'fun definition' =andgt; one hardware resource SAFL Properties magma:a structural HDL:  magma: a structural HDL Embedded in pure-functional ML Similar syntax and semantics (CBV) to SAFL Supports synthesis/simulation Uses ML functors to parameterise over different basis functions Synthesis == Static Expansion Only describes acyclic, combinatorial hardware no 'observable sharing' problems a magmaexample (1):  a magma example (1) functor RippleAdder (B:BASIS):RP_ADD = struct type bit=B.bit fun adder (x,y,c_in) = (B.xorb(c_in, B.xorb(x,y)), B.orb( B.orb( B.andb (x,y), B.andb(x,c_in)), B.andb(y,c_in))) Adder c_in x y c_out s_out a magmaexample (2):  a magma example (2) fun carry_chain f _ ([],[]) = [] | carry_chain f c_in (x::xs,y::ys) = let val (res_bit, c_out) = f (x,y,c_in) in res_bit::(carry_chain f c_out (xs,ys)) end val ripple_add = carry_chain adder B.b0 Adder x1 y1 b0 Adder x2 y2 Adder x3 y3 Adder Adder X4 y4 x5 y5 s_out1 s_out2 s_out3 s_out4 s_out5 a magmaexample (3):  a magma example (3) - structure SimulateAdder = RippleAdder (SimulationBasis); - SimulateAdder.ripple_add ([b1,b0,b0,b1,b1,b1],[b0,b1,b1,b0,b1,b1]) val it = [b1,b1,b1,b1,b0,b1] : SimulateAdder.bit list - structure SynthesiseAdder = RippleAdder (SynthesisBasis); - SynthesiseAdder.ripple_add (Magma.new_bus 5, Magma.new_bus 5) and(w_1,w_45,w_46); and(w_2,w_1,w_44); ... and(w_149,w_55,w_103); val it = ['w_149','w_150','w_151','w_152','w_153'] Support for simulation and synthesis: integratingSAFL and magma (1):  integrating SAFL and magma (1) andlt;% (* Magma code Library Block: ---------------------------------- *) signature RP_ADD = ... functor Magma_Code (B:BASIS):RP_ADD = ... Contains ripple adder spec (as before) %andgt; (* SAFL code: ------------------------------------------------- *) fun mult(x, y, acc) = if (x=0 | y=0) then acc else mult(xandlt;andlt;1, yandgt;andgt;1, if y[0] then andlt;% ripple_add %andgt;(acc,x) else acc) Magma fragments treated as SAFL-level functions integratingSAFL and magma (2):  integrating SAFL and magma (2) Encounter Magma Fragment Execute Magma under Synthesis Interpretation Process 2: SAFL Compiler Process 1: ML Session Magma Verilog [Time] andlt;% m %andgt;(e_1, …, e_k) integratingSAFL and magma (3):  integrating SAFL and magma (3) fun f(x) = andlt;% M %andgt;(x) + andlt;% M %andgt;(x) fun g(x) = andlt;% M %andgt;(x) fun f(x) = g(x) + g(x) RTL Verilog FPGA Source-level transformation High-level synthesis RTL synthesis case study:DES:  case study: DES SAFL Describes DES Algorithm Magma Describes Wiring Permutations Current Version Not Pipelined Making a pipelined version through SAFL/Magma program transformation is topic of future work Throughput of 15.8 Mb/sec On Altera APEX 200K FPGA with 33MHz clock Theoretical max clock speed design andgt; 40MHz 2 DES blocks + test harness =andgt; 17% of FPGA case study:DES – Dev Boad:  case study: DES – Dev Boad APEX E20K200E Status LEDs conclusions:  conclusions It is possible to combine behavioural + (limited) structural design in a clean way Fine-grained structure integrates well with SAFL’s notion of resource-awareness Program transformation remains a powerful technique for exploring tradeoffs Tested technique on a real-life case study ongoingresearch:  ongoing research Extending the SAFL Language ML-style references Many-many synchronous channels Pi-calculus style channel passing Extending the FLaSH tool-chain Developing / experimenting with new SAFL transformations Building SAFL compiler which targets asynchronous hardware Building larger examples

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