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Performing LispLUV 94 Tutorial

Kenneth R. Anderson BBN STD 6/4a 10 Moulton St. Cambridge, MA 02138 KAnderson@BBN.COM

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Some Questions

Q: Is Lisp Slow? A: No, Lisp can be as fast as C, even faster. Q: If Lisp is so fast, why is my application so slow? A: It is easy to write Lisp. It is easy to write slow Lisp. Q: If I write fast Lisp, will it look like C? A: Sometimes it can, but you can also use features unique to Lisp.

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You will learn

about performance issues in Lisp and other high level languages, like C and C++. how to identify performance problems in your software. how to avoid performance pitfalls.

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Performance

Performance is not the only -- or even the most important -- measure of a Lisp implementation. [RPG85, p.1] Performance problems are easily noticed. Other measures are less obvious, but become important in the long run. Clarity Explicit knowledge Extensibility Habitibility

How do we deliver such things, and performance?

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Rough Course Outline Performance myths persist. How do we learn slow Lisp? Understand the architecture of a Lisp system. Take a ruler to a spitting contest. Read the fine print. Your application is the ultimate benchmark. Performance expert systems. Delivering performance. Getting faster by getting higher.

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Spot Quiz1. Which is faster, A or B?Lisp A: (mod i 4) B: (logand i 3) (sort #(1 2 3 1 2 3 ...)) C i%4 i&3

2. Which is faster, Lisps SORT or Cs QSORT? 3. What is relative times of: (chaos 5 1) (chaos 5 0.33) (chaos 5 1/3) 1 ___ ___

(defun chaos (n x) (dotimes (i n) (setq x (+ 1 x (- (* x x)))) x))

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Robust Line Fit to 50 Points

Given a List of (x y) points, estimate a line fit as follows: Slope is the median of the slope between each pair of points. Intercept is the median of y - x*Slope of each point. Error is the median of the absolute value of the error of each point, error = y - (Intercept + x*Slope)

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Robust Line Fit to 50 points(defun median (sequence &optional (order #'>)) ;; Destructively sort SEQUENCE and return the median element. (setq sequence (sort sequence order)) (values (multiple-value-bind (n/2 remainder) (truncate (length sequence) 2) (if (zerop remainder) (* 0.5 (+ (elt sequence (1- n/2)) (elt sequence n/2))) (elt sequence n/2))) sequence)) (setq points (let ((points ())) (dotimes (i 50) (let ((p (random 100))) (push (list p (+ (* 2 p) (- (random 5) 2))) points))) points))

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What single change leads to the most improvement?(defun line-fit-1 (points) ;; Fits a robust line to a list of (x y) pairs, POINTS. ;; Returns intercept, slope, and median absolute error. (let* ((slope (median (mapcon #'(lambda (L) ; Slope of each pair of points. (let ((p1 (first L))) (mapcan #'(lambda (p2) (if (/= (first p2) (first p1)) (list (/ (- (second p2) (second p1)) (- (first p2) (first p1)))))) (rest L)))) points))) (intercept (median (mapcar #'(lambda (p) (- (second p) (* slope (first p)))) points))) (error (median (mapcar #'(lambda (p) (abs (- (second p) (+ (* slope (first p)) intercept)))) points)))) (values intercept slope error)))

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Myth: Lisp is slow because it is interpreted. Recent quotes:

Lisp, Smalltalk, and other interpreted languages ... [Udell] Interpreted languages, such as Smalltalk adapt this approach ... [Meyers] Often the complete system and the genetic operators themselves are written in an interpreting language like LISP [Koza 1992, Page 71]. This reduces performance in most hardware environments. [Nordin]

Many people only experience Lisp through an interpreter, such as EMACS. Lisp is compiled. Some modern Lisps dont have interpeters (MCL, Franz for Windows,Scheme) Lisp semantics described in terms of EVAL.

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Myth: Automatic garbage collection is slow.

Noticable pauses, often at the wrong time. But ephemeral GC make pauses quite short. Explict GC cost is hidden. With enough memory, GC becomes almost free [Appel]. Reference counting, can be quite costly (commonly advocated in C++). GC quite competitive with hand optimized methods [Zorn] However, consing is not free!

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Myth: Lisp is slow on stock hardware.

High performance Lisp implementations have existed for some time. Stock hardware does provide some support for non C languages. Stock hardware may provide less support for object oriented languages, like Smalltalk, C++ or Lisp [Zorn94] Branches less common. Indirect function calling (dispatch) more common.

RISC architectures generally match Lisp better than CISC because complex instructions may not match Lisp well [RAM93].

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Myth: Performance of low level languages is easier to estimate.

Estimates from C experts can vary by a factor of 5 [BKV]. Todays RISC computers make performance issues harder to expose. Register declarations in C are better made by the compiler.

C++ performance issues are much less clear than Cs. -> Smart pointers are neither. C++ overhead can be 30% - 100% of Cs.

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Myth: Recode in C or C++ to make your algorithm faster.

Recoding in general can make an algorithm faster because you think about it. Recoding for a parallel processor can make parallelization unnecessary.

Recoding in C requires declarations that could be added to Lisp just as easily. You are on your own for the hard stuff that the Lisp implementor provides. Recode in C, then recode in Lisp.

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Spot Quiz Results1. Which is faster, A or B?Lisp A: (mod i 4) B: (logand i 3) (sort #(1 2 3 1 2 3 ...)) C i%4 i&3 [Some Lisps]

2. Which is faster, Lisps SORT or Cs QSORT? 3. What is relative times of: (chaos 5 1) (chaos 5 0.33) (chaos 5 1/3) 1 6 400

(defun chaos (n x) (dotimes (i n) (setq x (+ 1 x (- (* x x)))) x))

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How do we learn slow Lisp?

Lisp programming is easy, but only to a point [RGB91]. In Lisp, writing a slow program is easy. C programming is difficult. Programmer provides all the details (declaration). Few datatypes.

In C writing a slow program is almost impossible.

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How do we learn slow Lisp? Simple object model. Everything is an object. Functions operate on objects.

Uniform cost assumption. ELT works on any sequence O(1), or O(n).

Mapping style garden path.

(mapcar #feature objects) ; Maybe OK. (reduce #+ (mapcar #square (mapcar #x-pos data)) ; YOW! (remove-duplicates (apply #append (mapcar #attributes objects)) ; YOW!

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How do we learn slow Lisp? SETF vs SET EQUAL vs EQ ELT vs AREF APPLY vs FUNCALL READ-FROM-STRING vs INTERN

Learn general (~ equivalent) subset of Lisp.

Overly general interface bug. Lots of keyword and optional arguments. Lots of hooks. Lots of methods to override.

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How do we learn slow Lisp? Suffiently smart compiler bug. (dotimes (i N) (foo i)) ; Is i a fixnum? (length (the array a)) ; Is length inlined? (+ (the fixnum i) (the fixnum j)) ; Is + inlined?

Bad declaration bug.(declare (type (array fixnum *) a1 a2 a3) (declare (type (simple-array t *) a1 a2 a3)

Inappropriate data structures Matrix multiply with matrix as nested lists. Long division with roman numerals [Allen].

Lisp (almost) lets you forget about computer science. Easy to do things that are hard in other languages. Lets you worry about the details later. The ultimate time space tradeoff.

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Levels of Lisp System Architecture Hardware Level Lisp Instruction Level Variable/constant reference Free/Special Variable lookup and binding Function Call/Return Data structure manipulation Type computation Arithmetic

Lisp operation level MAPCAR, ASSOC, APPEND, REVERSE

Major facilities Interpreter I/O Garbage Collection Compiler

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Objects Lisp Variables can have variable type at run time. All objects have a type at runtime. Objects are passed to functions.

C++

Variables have a fixed type at compile time. Primitive objects have no runtime type information. User defined classes have type identity only for method dispatch and exception handling. Runtime type information (RTTI) must be provided by the user. Objects are passed to functions by Copying Pointer Reference

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Object RepresentationsPointer Pointer Header Data

+ Obvious representation for C or C++. - Level of indirection. - Objects are fatter. - Type check requires page reference.

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Object Representations (cont.)Object description Header? Pointer Tag CDR CAR Data

Immediate Object Description Data Tag

+ Some type info without page reference. + Small, immediate objects. + Some indirect objects without header (cons). +/- Tag manipulation required, but can be combined with access.

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Object Representation (cont.)BIBOP - Big Bag of Pages Header

512 Byte Page

Pointer

Data

+ No per object header. - Type check requires page reference.

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Object Representation (cont.)Object Table Header Header Header Pointer Pointer Pointer data data

. . .

+ Two levels (types) of storage management can be used. - Extra level of indirection.

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MCL Type Tags

000 Fixnum 001 Uvector - vectors, structures, instances 010 Symbol 011 Double-float 100 Cons, Nil 101 Short-float 110 Function 111 Immediate - Characters, and others.

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Allegro type tags000 Even fixnum 001 List 010 Other 100 Odd fixnum 101 Nil 110 Char 111 Symbol

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Allegro primitive operations

GetTag(v) (long) v & 7 FixnumToInt(v) v >> 2 IntToFixnum(v) v > 3) CharToSchar(v) (LispVal) ((((int) v)