An Architecture for Combinator Graph Reduction by Philip John Koopman Jr.

By Philip John Koopman Jr.

This e-book combines structure with implementation concepts for complex programming languages

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It also eliminates a conditional analysis that would otherwise be required to decide whether the I node is at the top of a subtree, in which case the address of the parent cell may not be available for rewriting in the TIGRE evaluation scheme. Chapter 4. Implementation of the TIGRE Machine 38 The K combinator is defined in TIGRE as: mov RO, pop(2) thread ip Thus, we see that the operation of I and K are almost identical if viewed in the proper manner. In other graph reducers, the K combinator rewrites a node to eliminate the reference to the second input argument.

The code for U is as follows: mov Rl, ip evaluate allocate 1 mov RO, ip mov ip, LtempO mov Rresult, Rl mov Lresult, result mov Rresult, RtempO top (RtempO) thread The allocation is performed after the evaluation, because the evaluation may disrupt the contents of any heap node pointer registers, and may trigger a garbage collection cycle. y f X Figure 4-8. The U combinator. 4. Supercombinators The compilation of supercombinator definitions for TIGRE is supported by the same set of primitives used to implement the Turner Set.

E. 01 53500 82900 Table 5-8. 0. 58 Chapter 5. TIGRE Performance functional language that does not directly support lazy evaluation). 0 running on a Sun 3/75 in elapsed time. 0 performance (and, TIGRE would be faster if an assembly language implementation were available for the Sun). 2. Imperative Language: MIPS R2000 C Compiler Of course, the ultimate speed comparison is one with a mainstream imperative language such as C. If combinator reduction can (some day) be made approximately as fast as C program execution, then lazy funcĀ­ tional programming or some other programming style that maps onto combinator reduction may become viable for widespread use in production programming.

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