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Dynamic Partial Evaluation

Dynamic Partial Evaluation. Gregory T. Sullivan MIT AI Lab gregs@ai.mit.edu. The Challenge. Metaobject protocols - reflection plus dynamism (as opposed to Java reflection). MOP  More indirection, less optimization (ouch!) How to optimize when, in principle, everything may change?.

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Dynamic Partial Evaluation

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  1. Dynamic Partial Evaluation Gregory T. Sullivan MIT AI Lab gregs@ai.mit.edu

  2. The Challenge • Metaobject protocols - reflection plus dynamism (as opposed to Java reflection). • MOP  More indirection, less optimization (ouch!) • How to optimize when, in principle, everything may change? Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  3. The Solution • Optimize at Runtime. • Optimize Optimistically. • JIT approach: “traditional” - (re)analyze, regenerate • analysis walks the code. • Dynamic PE: gather data as code is executed • execution walks the code. • Motto: “Don’t Model -- Observe.” Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  4. eq(GF42) T T l1=find-applicable-methods(foo, x, y); foo1(Point, Point), foo2(Line, Line), foo3(ColorPoint, ColorPoint) l2=generic-methods(foo); eq(l2) instance?(x, Point); instance?(x, Line); instance?(x, ColorPoint); true ,false ,true Bool Bool Bool instance?(y, Point); instance?(y, Line); instance?(y, ColorPoint); true ,false ,true Bool Bool Bool foo1(Point, Point), foo3(ColorPoint, ColorPoint) l1= list(fun) l3=sort-applicable-methods(l1) foo3(ColorPoint, ColorPoint), foo1(Point, Point), list(fun) f=first(l3) foo3(ColorPoint, ColorPoint) fun direct-call(f, x, y); Ex: Method Dispatch With a MOP Env = fooGF42 , xCP101 , yCP302 dyn-call(foo, x, y); Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  5. Example, Continued Env = fooGF42 , xCP101 , yCP302 eq(GF42) ColorPoint ColorPoint dyn-call(foo, x, y); l1=find-applicable-methods(foo, x, y); foo1(Point, Point), foo2(Line, Line), foo3(ColorPoint, ColorPoint) l2=generic-methods(foo); eq(l2) instance?(x, Point); instance?(x, Line); instance?(x, ColorPoint); true ,false ,true eq(true) eq(false) eq(true) instance?(y, Point); instance?(y, Line); instance?(y, ColorPoint); true ,false ,true eq(true) eq(false) eq(true) foo1(Point, Point), foo3(ColorPoint, ColorPoint) l1= eq(l1) l3=sort-applicable-methods(l2) foo3(ColorPoint, ColorPoint), foo1(Point, Point), eq(l3) f=first(l3) foo3(ColorPoint, ColorPoint) eq(foo3) direct-call(f, x, y); Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  6. Example, Continued Two Scenarios • Straight Optimization fun bar (x : ColorPoint, y : ColorPoint) dyn-call(foo, x, y); rewrites to fun bar (x : ColorPoint, y : ColorPoint) direct-call(foo3, x, y); // or inline • Profile-based method customization fun bar (x : Object, y : Object) dyn-call(foo, x, y); adds a new method add-fun bar (x : ColorPoint, y : ColorPoint) direct-call(foo3, x, y); // or inline Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  7. Machinery • Updating runtime with optimized methods. • we use generic functions and multiple dispatch. • Extended values: [regular value, expression, type] • environment maps ids to extended values. • Eval(exp, env)  [value, exp’, type] • (residual) expression represents “in the current environment, this expression will produce this value”. • the type encodes “what we can assume” when using this value. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  8. Context • Dynamic Virtual Machine (DVM) • Multiple dispatch, dynamically typed, subtypes, highly reflective, predicate types. • “Native” language DVML: Scheme plus types, generic functions, cells Caveats • Only a prototype so far. Paper • DVM, a dynamically-typed lambda-calculus with generic functions and subtyping. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  9. Dynamic PE for Expressions • Literals: { n }  [n, { n }, eq(n)] • Variable reference: { x }if Env(x)  V  [v, -, eq(v)], and v is expressible as a literal, return [v, {v}, eq(v)]else return V. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  10. Conditional Expressions { if e0 then e1 else e2 }, e0 V0  [v0, e’0, t0],if true?(v0) and e1 V  [v, e’1, t], • If v0 is fully static, eliminate the if & return V. • If v0 is not static, must rebuild conditional: return [v, {if e’0 then e’1 else e2}, T]. No info. about type. • Likewise for false and e2. * * Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  11. Some Details • This amounts to inlining, and is done heuristically. • Must handle conflicting bindings, closed-over variables. • Primitive functions handled specially. Call expressions * {call e0 e1 ... en}, ei Vi  [vi, e’i, ti], v0 = (xi : txi . ef):tf, check!(vi, txi) ef[xi[vi, e’i,glb(ti, txi)]]  V  [v, e’, t] * • If V0 not static, return [v, {call e’0e’1 ... e’n}, T]. • If V0 static, may return [v, e’, glb(t,tf)]. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  12. Generic Function Call {gf-call e0 e1 ... en}, ei Vi  [vi, e’i, ti], v0 = {f1,...,fm}, find-mam(f1,...,fm,V1...Vn)= [(xi : txi . ef):tf, static?](spec?, spec-types) = choose-spec(V0...Vn)arg-typei = if spec? spec-types[i] else glb(ti, txi) ef[xi[vi, e’i,arg-typei]]  V  [v, e, t] selection relies only on static types? • if spec?, add-method(v0, (xi : spec-types[i] . e):tf) • if V0 static and static?, fold as in non-generic function call. • if V0 static and not static?, [v, {gf-call e’0...e’n}, restype(v0)] Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  13. Swept Under the Rug Earlier dyn-call(foo,x,y)  direct-call(foo3,x,y) • Depends on foo’s method set staying constant. Also, other elements of MOP. • Runtime PE must track dependencies on generic function method sets and cells. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  14. Ex: Reflection in Java • From Braux & Noyé, PEPM00 public static void dumpFields(Object anObj) throws java.lang.IllegalAccessException { Field[] fields = anObj.getClass().getFields(); for (int i = 0; i < fields.length; i++) System.out.println(fields[i].getName()+“: “ +fields[i].get(anObj)); } specialized to Point class, should yield: public static void dumpFieldsPoint(Point anObj) { System.out.println(“x: “+anObj.x); System.out.println(“y: “+anObj.y); } Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  15. MOP Dynamic PE -- What It’s Best At • Collapsing indirection. • Removing dynamic type checks. gf-call(g, v)  call(f, v) + dependencies call(f, v) Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  16. Future Work • Tuning • when to specialize? • minimize overhead, gauge performance. • Gotchas: • customization introducing ambiguity • mutual recursion/specialization • Applied at machine code level? Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  17. The End • http://www.ai.mit.edu/~gregs/dynamic-pe.html Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

  18. Harnessing Dynamic PE • Suppose foo(x : Object){e} called with x a Point. • Run e with x  [-,-,Point] and get [v,e’,t], • Can define foo(x : Point){ e’ }. • But ...Where to put it? How to use it? • Generic function: contains a set of methods. • Multiple dispatch: chooses the most applicable based on types of all arguments. Dynamic Partial Evaluation - Greg Sullivan - NEPLS - December 7, 2000

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