Key Words and Phrases: real-time, compacting, garbage collection, list processing, virtual memory, file or database management, storage management, storage allocation, LISP, CDR-coding, reference counting.
CR Categories: 3.50, 3.60, 373, 3.80, 4.13, 24.32, 433, 4.35, 4.49
This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522.A real-time list processing system is one in which the time required by each elementary list operation (CONS, CAR, CDR, RPLACA, RPLACD, EQ, and ATOM in LISP) is bounded by a (small) constant. Classical list processing systems such as LISP do not have this property because a call to CONS may invoke the garbage collector which requires time proportional to the number of accessible cells to finish. The space requirement of a classical LISP system with N accessible cells under equilibrium conditions is (1.5+μ)N or (1+μ)N, depending upon whether a stack is required for the garbage collector, where μ>0 is typically less than 2.
A list processing system is presented which:
1) is real-time--i.e. T(CONS) is bounded by a constant independent of the number of cells in use;
2) requires space (2+2μ)N, i.e. not more than twice that of a classical system;
3) runs on a serial computer without a time-sharing clock;
4) handles directed cycles in the data structures;
5) is fast--the average time for each operation is about the same as with normal garbage collection;
6) compacts--minimizes the working set;
7) keeps the free pool in one contiguous block--objects of nonuniform size pose no problem;
8) uses one phase incremental collection--no separate mark, sweep, relocate phases;
9) requires no garbage collector stack;
10) requires no "mark bits", per se;
11) is simple--suitable for microcoded implementation.
Extensions of the system to handle a user program stack, compact list representation ("CDR-coding"), arrays of non-uniform size, and hash linking are discussed. CDR-coding is shown to reduce memory requirements for N LISP cells to ≈(I+μ)N. Our system is also compared with another approach to the real-time storage management problem, reference counting, and reference counting is shown to be neither competitive with our system when speed of allocation is critical, nor compatible, in the sense that a system with both forms of garbage collection is worse than our pure one.MIT Artificial Intelligence Laboratory
Department of Defense Advanced Research Projects Agenc
