This paper presents key insights and design rationales behind Inferno, a functional simulation construction framework developed at Intel to support execution-driven cycle-accurate performance modeling and simulation of advanced microarchitectural data speculation techniques for future processor designs and explorations. Inferno divides the task of functional simulation into three essential components, namely: (1) context manager of in-flight speculatively executed instructions, (2) stateless emulator of instruction semantics, and (3) a high speed functional simulator capable of booting OS and running large-scale system workloads. These building block components work together in concert via a set of well-architected functional model convergence APIs. With a novel abstraction called speculative domain, the context manager serves effectively as a relational database about the in-flight instructions and on-going speculations. Through a set of functional model usage APIs, the context manager enables performance models to express arbitrary microarchitectural data speculation scenarios. The contribution of this paper is to demonstrate the importance of providing a functional model with modular construction, proper abstraction and expressive APIs for speculative state management. Inferno is such a functional model construction framework and has significantly improved productivity in modeling a variety of sophisticated data speculation microarchitecture techniques.

This paper proposes to use a logical hypercube structure for detecting message stability in distributed systems. In particular, a stability detection protocol that uses such a superimposed logical structure is presented, and its scalability is compared with other known stability detection protocols. The main benefits of the logical hypercube approach are scalability, fault-tolerance, and refraining from overloading a single node or link in the system. These benefits become evident both by an analytical comparison and by simulations. Another important feature of the logical hypercube approach is that the performance of the protocol is in general not sensitive to the topology of the underlying physical network.

This paper proposes to use a logical hypercube structure for detecting message stability in distributed systems. In particular, a stability detection protocol that uses such a superimposed logical structure is presented, and its scalability is compared with other known stability detection protocols. The main benefits of the logical hypercube approach are scalability, fault-tolerance, and refraining from overloading a single node or link in the system. These benefits become evident both by an analytical comparison and by simulations. Another important feature of the logical hypercube approach is that the performance of the protocol is in general not sensitive to the topology of the underlying physical network.