Two formal models for parallel computation are presented: an abstract conceptual model and a parallel-program model. The former model does not distinguish between control and data states. The latter model includes the capability for the representation of an infinite set of control states by allowing there to be arbitrarily many instruction pointers (or processes) executing the program. An induction principle is presented which treats the control and data state sets on the same ground. Through the use of “place variables,” it is observed that certain correctness conditions can be expressed without enumeration of the set of all possible control states. Examples are presented in which the induction principle is used to demonstrate proofs of mutual exclusion. It is shown that assertions-oriented proof methods are special cases of the induction principle. A special case of the assertions method, which is called parallel place assertions, is shown to be incomplete. A formalization of “deadlock” is then presented. The concept of a “norm” is introduced, which yields an extension, to the deadlock problem, of Floyd's technique for proving termination. Also discussed is an extension of the program model which allows each process to have its own local variables and permits shared global variables. Correctness of certain forms of implementation is also discussed. An Appendix is included which relates this work to previous work on the satisfiability of certain logical formulas.

The problem of searching the set of keys in a file to find a key which is closest to a given query key is discussed. After “closest,” in terms of a metric on the the key space, is suitably defined, three file structures are presented together with their corresponding search algorithms, which are intended to reduce the number of comparisons required to achieve the desired result. These methods are derived using certain inequalities satisfied by metrics and by graph-theoretic concepts. Some empirical results are presented which compare the efficiency of the methods.

No abstract

When talking about blockchain technology in academia, business, and society, frequently generalizations are still heared about its-supposedly inherent-enormous energy consumption. This perception inevitably raises concerns about the further adoption of blockchain technology, a fact that inhibits rapid uptake of what is widely considered to be a groundbreaking and disruptive innovation. However, blockchain technology is far from homogeneous, meaning that blanket statements about its energy consumption should be reviewed with care. The article is meant to bring clarity to the topic in a holistic fashion, looking beyond claims regarding the energy consumption of Bitcoin, which have, so far, dominated the discussion.