We present a theory for modular refinement of Synchronous Sequential Circuits (SSMs) using Bounded Dataflow Networks (BDNs). We provide a procedure for implementing any SSM into an LI-BDN, a special class of BDNs with some good compositional properties. We show that the Latency-Insensitive property of LI-BDNs is preserved under parallel and iterative composition of LI-BDNs. Our theory permits one to make arbitrary cuts in an SSM and turn each of the parts into LI-BDNs without affecting the overall functionality. We can further refine each constituent LI-BDN into another LI-BDN which may take different number of cycles to compute. If the constituent LI-BDN is refined correctly we guarantee that the overall behavior would be cycle-accurate wi...
Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effectiv...
Abstract — Synchronous Dataflow (SDF) is a well-known model of computation for dataflow-oriented app...
We present a translation from programs expressed in a functional IR into dataflow networks as an int...
We present a technique for implementing dataflow networks as compositional hardware circuits. We fir...
International audienceIn this paper, we address the following problem: given a synchronous digital c...
Synchronous dataflow (SDF) semantics are wellsuited to representing and compiling multirate signal p...
This paper presents efficient reencoding and resynthesis algorithms for cycle-time minimization of m...
We formally define - at the stream transformer level - a class of synchronous circuits that tolerate...
This paper addresses the question of producing modular sequential imperative code from synchronous d...
This paper presents a transformation scheme from Boolean-controlled dataflow (BDF) networks to Petri...
This paper introduces a technique, called resynchronization, for reducing synchronization overhead i...
AbstractThis paper addresses the problem of using a dataflow language in “real-time” continuously op...
Abstract—A ‘natural ’ way of describing an algorithm is as a data flow. When synthesizing hardware a...
For time-sensitive networks, as in the context of IEEE TSN and IETF Detnet, cyclic dependencies are ...
Abstract. Synchronous Data Flow Graphs (SDFGs) have proven to be suitable for specifying and analyzi...
Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effectiv...
Abstract — Synchronous Dataflow (SDF) is a well-known model of computation for dataflow-oriented app...
We present a translation from programs expressed in a functional IR into dataflow networks as an int...
We present a technique for implementing dataflow networks as compositional hardware circuits. We fir...
International audienceIn this paper, we address the following problem: given a synchronous digital c...
Synchronous dataflow (SDF) semantics are wellsuited to representing and compiling multirate signal p...
This paper presents efficient reencoding and resynthesis algorithms for cycle-time minimization of m...
We formally define - at the stream transformer level - a class of synchronous circuits that tolerate...
This paper addresses the question of producing modular sequential imperative code from synchronous d...
This paper presents a transformation scheme from Boolean-controlled dataflow (BDF) networks to Petri...
This paper introduces a technique, called resynchronization, for reducing synchronization overhead i...
AbstractThis paper addresses the problem of using a dataflow language in “real-time” continuously op...
Abstract—A ‘natural ’ way of describing an algorithm is as a data flow. When synthesizing hardware a...
For time-sensitive networks, as in the context of IEEE TSN and IETF Detnet, cyclic dependencies are ...
Abstract. Synchronous Data Flow Graphs (SDFGs) have proven to be suitable for specifying and analyzi...
Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effectiv...
Abstract — Synchronous Dataflow (SDF) is a well-known model of computation for dataflow-oriented app...
We present a translation from programs expressed in a functional IR into dataflow networks as an int...