D3-machine: A decoupled data-driven multithreaded architecture with variable resolution support

Abstract

This paper presents the Decoupled Data-Driven machine (D3-machine), a multithreaded architecture with data-driven synchronization. The D3-machine is an efficient and cost-effective design that combines the advantages of the data-driven synchronization with those of Instruction Level Parallelism (ILP). Two major design ideas are utilized by the proposed model: asynchronous execution of synchronization and computation operations and multithreaded graphs with variable resolution. The guiding principle in the generation of the threads is to fully exploit the ILP capabilities of the target processor. The entire dynamic Data-Flow (DF) graph is mapped by a one-to-one function onto the virtual space of the machine. Thus, the traditional DF graph operations (synchronization) of token matching and token formatting/routing are reduced into memory access operations. This allows us to utilize the dynamic DF principles, that exploit ultimate parallelism, for thread scheduling at a hardware minimal cost. With a combination of deterministic and stochastic simulation experiments is shown that the D3-machine has the necessary attributes for efficient parallel processing

it can tolerate long latencies, exploit parallelism, and also benefit from locality. Furthermore, by decoupling the synchronization portion of a thread from the computation, the D3-machine effectively neutralizes the overhead associated with dynamic DF scheduling. © 2001 Elsevier Science B.V.