Elaheh Bozorgzadeh

Instruction generation for hybrid reconfigurable systems

We present an algorithm for simultaneous template generation and matching. The algorithm profiles the graph and iteratively contracts edges to create the templates. The algorithm is general and can be applied to any type of graph, including directed graphs and hypergraphs. We discuss how to target the algorithm towards the novel problem of instruction generation and selection for a hybrid (re)configurable systems. In particular, we target the strategically programmable system, which embeds complex computational units like ALUs, IP blocks, etc. into a configurable fabric. We argue that an essential compilation step for these systems is instruction generation, as it is needed to specify the functionality of the embedded computational units. Additionally, instruction generation can be used to create soft macros tightly sequenced pre-specified operations placed in the configurable fabric.

Pattern routing: use and theory for increasing predictability and avoiding coupling

Deep submicron effects, along with increasing interconnect densities, have increased the complexity of the routing problem. Whereas previously we could focus on minimizing wirelength, we must now consider a variety of objectives during routing. For example, an increased amount of timing restrictions means that we must minimize interconnect delay. But, interconnect delay is no longer simply related to wirelength. Coupling capacitance has become a dominant component of delay due to the shrinking of device sizes. Regardless, the most important objective is producing a routable circuit. Unfortunately, this often conflicts with minimizing interconnect delay as minimum delay routes create congested areas, for which an exact routing cannot be realized without violating design rules. In this work, we use the concept of pattern routing to develop algorithms that guide the router to a solution that minimizes interconnect delay - by considering both coupling and wirelength-without damaging the routability of the circuit. The paper is divided into two parts. The first part demonstrates that pattern routing can be used without affecting the routability of the circuit. We propose two schemes to choose a set of nets to pattern route. Using these schemes, we show that the routability is not hindered. The second part builds on the previous part by presenting a framework for coupling reduction using pattern routing. We develop theory and algorithms relating pattern routing and coupling. Additionally, we give suggestions on how to extend our theory and use our algorithms for both global and detailed routing.

Physically-aware HW-SW partitioning for reconfigurable architectures with partial dynamic reconfiguration

Many reconfigurable architectures offer partial dynamic configurability, but current system-level tools cannot guarantee feasible implementations when exploiting this feature. We present a physically aware hardware-software (HW-SW) scheme for minimizing application execution time under HW resource constraints, where the HW is a reconfigurable architecture with partial dynamic reconfiguration capability. Such architectures impose strict placement constraints that lead to implementation infeasibility of even optimal scheduling formulations that ignore the nature of these constraints. We propose an exact and a heuristic formulation that simultaneously partition, schedule, and do linear placement of tasks on such architectures. With our exact formulation, we prove the critical nature of placement constraints. We demonstrate that our heuristic generates high-quality schedules by comparing the results with the exact formulation for small tests and a popular, but placement-unaware scheduling heuristic for larger tests. With a case study, we demonstrate extension of our approach to handle heterogenous architectures with specialized resources distributed between general purpose programmable logic columns. The execution time of our heuristic is very reasonable - task graphs with hundreds of nodes are processed in a couple of minutes.

Integrating Physical Constraints in HW-SW Partitioning for Architectures With Partial Dynamic Reconfiguration

Partial dynamic reconfiguration is a key feature of modern reconfigurable architectures such as the Xilinx Virtex series of devices. However, this capability imposes strict placement constraints such that even exact system-level partitioning (and scheduling) formulations are not guaranteed to be physically realizable due to placement infeasibility. We first present an exact approach for hardware-software (HW-SW) partitioning that guarantees correctness of implementation by considering placement implications as an integral aspect of HW-SW partitioning. Our exact approach is based on integer linear programming (ILP) and considers key issues such as configuration prefetch for minimizing schedule length on the target single-context device. Next, we present a physically aware HW-SW partitioning heuristic that simultaneously partitions, schedules, and does linear placement of tasks on such devices. With the exact formulation, we confirm the necessity of physically-aware HW-SW partitioning for the target architecture. We demonstrate that our heuristic generates high-quality schedules by comparing the results with the exact formulation for small tests and with a popular, but placement-uanaware scheduling heuristic for a large set of over a hundred tests. Our final set of experiments is a case study of JPEG encoding-we demonstrate that our focus on physical considerations along with our consideration of multiple task implementation points enables our approach to be easily extended to handle heterogenous architectures (with specialized resources distributed between general purpose programmable logic columns). The execution time of our heuristic is very reasonable-task graphs with hundreds of nodes are processed (partitioned, scheduled, and placed) in a couple of minutes

Floorplan-aware automated synthesis of bus-based communication architectures

As system-on-chip (SoC) designs become more complex, it is becoming harder to design communication architectures to handle the ever increasing volumes of inter-component communication. Manual traversal of the vast communication design space to synthesize a communication architecture that meets performance requirements becomes infeasible. In this paper, we address this problem by proposing an automated approach for synthesizing cost-effective, bus-based communication architectures that satisfy the performance constraints in a design. Our synthesis flow also incorporates a high-level floorplanning and wire delay estimation engine to evaluate the feasibility of the synthesized bus architecture and detect timing violations early in the design flow. We present case studies of network communication SoC subsystems for which we synthesized bus architectures, detected timing violations and generated core placements in a matter of hours instead of several days it took for a manual effort.

RPack: routability-driven packing for cluster-based FPGAs

Routing tools consume a significant portion of the total design time. Considering routability at earlier steps of the CAD flow would both yield better quality and faster design process. In this paper we are presenting a routability-driven clustering method for cluster-based FPGAs. Our method packs LUTs into logic clusters while incorporating routability metrics into a cost function. The objective is to minimize this routability cost function . Our cost function is consistently able to indicate improved routability. Our method yields up to 50 % improvement over existing clustering methods in terms of the number of routing tracks required. The average improvement obtained is 16.5 %. Reduction in number of tracks yields reduced routing area.

A super-scheduler for embedded reconfigurable systems

Emerging reconfigurable systems attain high performance with embedded optimized cores. For mapping designs on such special architectures, synthesis tools, that are aware of the special capabilities of the underlying architecture are necessary. We propose an algorithm to perform simultaneous scheduling and binding, targeting embedded reconfigurable systems. The algorithm differs from traditional scheduling methods in its capability of efficiently utilizing embedded blocks within the reconfigurable system. The algorithm can be used to implement several other scheduling techniques, such as ASAP, ALAP, and list scheduling. Hence we refer to it as a super-scheduler. The algorithm is a path-based scheduling algorithm. At each step, an individual path from the input DFG is scheduled. The experiments with several DFGs extracted from MediaBench suite indicate promising results. The scheduler presents the capability to perform the trade-off between maximally utilizing the high-performance embedded blocks and exploiting parallelism in the schedule.

A unified theory of timing budget management

This work presents a theoretical framework that optimally solves many open problems in time budgeting. Our approach unifies a large class of existing time-management paradigms. Examples include time budgeting for maximizing total weighted delay relaxation, minimizing the maximum relaxation and min-skew time budget distribution. We show that many of the time management problems can be transformed into a min-cost flow instance that can be optimally and efficiently solved through well-known combinatorial techniques. Experiments include mapping of several designs, which are implemented using parameterized CoreGen IP cores, on Xilinx FPGA devices. Different time budgeting policies have been applied during the mapping stage. Our time management techniques always improved the area requirement of the implemented testbenches compared to a widely-used path-based method. We also compared the maximum budgeting and fairness in delay budget assignments. Our experimental results show that an average improvement of 19% in area can be achieved when fairness and maximum budgeting policies are combined, compared to pure maximum budgeting.

ROUTABILITY-DRIVEN PACKING: METRICS AND ALGORITHMS FOR CLUSTER-BASED FPGAs

Most of the FPGAs area and delay are due to routing. Considering routability at earlier steps of the CAD flow would both yield better quality and faster design process. In this paper, we discuss the metrics that affect routability in packing logic into clusters. We are presenting a routability-driven clustering method for cluster-based FPGAs. Our method packs LUTs into logic clusters while incorporating routability metrics into a cost function. Based on our routability model, the routability in timing-driven packing algorithm is analyzed. We integrate our routability model into a timing-driven packing algorithm. Our method yields up to 50% improvement in terms of the minimum number of routing tracks compared to VPack (16.5% on average). The average routing area improvement is 27% over VPack and 12% over t-VPack.

An exact algorithm for coupling-free routing

In this wrok, we develop methods to reduce interconnect delay and noise caused by coupling. First, we explain the Coupling-Free Routing (CFR) problem. CFR takes a set of nets and tries to find a one-bend couple-free routing for a subset of nets. A routed net must not couple with any other routed net. We define coupling as a boolean variable which is true when the coupling of two nets is greater than some threshold. Any pair-wise coupling definition can be used. We argue that this problem is useful in both global and detailed routing We develop an exact algorithm for the CFR decision problem via a transformation to 2-satisfiability. This algorithm runs in linear time. The decision problem determines whether the given set of nets is coupling-free routable. Next, we present the implication graph which models the dependencies associated with CFR. Also, we look at some of the properties associated with the graph. Finally, we develop a new algorithm for the Maximum Coupling-Free Layout (MAX-CFL) problem. Given a set of nets, the MAX-CFL is defined as finding a subset of nets that are coupling-free routable. The subset should have maximum size and/or critically. The new algorithm, called implication algorithm, uses properties assoicated with the implication graph and experiments show that it consistently finds the best solution in terms of number of nets routed as compared to previous algorithms