The FPGA-Based Prototyping Methodology Manual: Best practices in You can download a FREE, full eBook edition (English tadocarlandchan.tk,.prc tadocarlandchan.tk and. Freescale Semiconductor Corporation. “In addition to our stated goals of protocol testing, our FPGA system prototype delivered project schedule acceleration in. Methodology Manual For FPGA-Based Prototyping Is Win-Win. workshops based on the FPGA-based Prototyping Methodology Manual (FPMM) in /12, I.
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Manual Best Practices In Design-for- prototyping Pdf. FPGA-based Prototyping Methodology Manual 1 Synopsys Introducing. Manual(FPMM)Best Practices . Introducing the FPMM: FPGA-Based Prototyping Methodology Manual. • Launch of new online community for prototyping. • Concept. This book collects the best practices FPGA-based Prototyping of SoC and ASIC devices into one place for the first time, drawing upon not only.
This book collects the best practices FPGA-based Prototyping of SoC and ASIC devices into one place for the first time, drawing upon not only the authors' own knowledge but also from leading practitioners worldwide in order to present a snapshot of best practices today and possibilities for the future. Read more Read less. Customers who viewed this item also viewed. Page 1 of 1 Start over Page 1 of 1. Pong P. Customers who bought related items also bought. Verilog by Example: Vhdl By Example.
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Material is well covered. A bit dated but very useful for someone wanting to learn about FPGA and it application in prototyping. Book was sent within a god time frame.
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Get fast, free shipping with site Prime. Back to top. Get to Know Us. site Payment Products. In this technique, all the signals are multiplexed, without promoting the signals on the critical path.
Some critical signals may not be multiplexed to obtain a better performance in terms of system frequency. Another disadvantage related to the combinational loops is that any unpredictable delay of an inter-FPGA signal causes the transmission of nonupdated values and then system errors. Even though such a sophisticated approach may realize faster verification speed, it decreases the reliability of circuit verification which is the most critical issue of circuit verification.
In [ 15 , 16 ], the authors proposed a new multiplexing approach based on the integer linear programming. The main objective of this study is to select which signals must be multiplexed and those which must not. Using this technique, all signals are transmitted on each phase, but only those with updated values are considered.
Since all the signals are transmitted in each phase, the number of slots per phase increases and the system frequency is decreased. This technique, as the one in [ 9 , 10 ], uses a constructive routing algorithm which is not optimized. In fact, when a signal is already routed, it cannot be rerouted to leave the routing resources currently used to another signal that has the greatest need for these resources.
This disadvantage will be solved using an iterative routing algorithm as proposed in this study. In fact, the objective of our iterative approach is that all the signals negotiate the use of the routing resources.
Each physical wire will be used by the signal which has the biggest need to this resource. This negotiation will be done through several iterations to solve all the conflicts, unlike the constructive routing algorithm which is done only by one iteration. Figure 1 presents the prototyping flow. Figure 1: Prototyping flow.
In this paper, the benchmarks are synthesized with the Synplify industrial tool [ 18 ]. The output of this task is a postsynthesis Verilog netlist. Partitioning After mapping the netlist onto the target technology, it is divided into partitions; each can fit into a single target FPGA.
The partitioner performs K-way partitioning with multiobjective function. The partitioning step is very critical since it has a significant impact on the performance of the prototyping system.
In this study, we use the Wasga partitioning tool of Flexras technologies [ 19 ]. For this tool, we set some constraints in order to have a good trade-off between the following criteria. For big designs, it is difficult, if not impossible, to find a partitioning solution which meets the constraint related to the number of physical connections between FPGAs.
As will be explained subsequently, the solution is to make a postpartitioning process allowing a number of signals to share the same physical wire in different time fractions. The insertion of these multiplexers increases the delays on combinatorial paths. These delays are correlated to the number of multiplexed signals multiplexing ratio.
Thus, the main goal of the partitioner is to reduce the number of the cut signals in order to get the lowest rate of multiplexing.
On the other side, the ratio between the number of cut signals and the number of available wires should be balanced between all pairs of FPGA. Therefore, the objective of the partitioning tool is to minimize the parameter presented in being the number of FPGA pairs in the prototyping platform, being the number of signals between the pair of FPGAs, and being the number of available tracks between the same pair.
Finally, the partitioner aims to provide guidance about the signals which should not be multiplexed since they affect the critical path. The system frequency is imposed by the delay of the longest combinatorial path between two registers. The delay on a combinatorial path is strongly correlated with the number of times a path crosses the border of an FPGA, called combinatorial hop.
Therefore, it is important to absorb the signals belonging to the critical combinatorial paths. In Figure 2 a , the number of combinatorial hops is equal to 2, and the number of cut signals is equal to 2. If the partitioner identifies the best module to move, the partitioning solution will be improved since the number of inter-FPGA signals and the number of combinatorial hops will be reduced as shown in Figure 2 b.
Figure 2: Combinatorial hop example. The number of logical resources in the FPGA circuits is limited. During the partitioning, an occupancy rate constraint is set, so the partitioning tool must take into account this number and try to make a partitioning solution which meets the available resources. The occupancy rate should consider the additional logical area which will be occupied by the multiplexing IPs after the inter-FPGA routing tasks. Unlike most of commercial tools, the partitioning tool used in our experiments operates on synthesized netlists which gives accurate information about the size of the design so it can meet the available logical resources of each FPGA.
Routing and Multiplexing The system clock is the clock of the logic design being prototyped. The system clock period is divided into a number of slots as shown in Figure 3.
Each signal is transmitted between a pair of FPGA within one slot period. Figure 3: Clocking framework. The system clock period is given by the following equation: and correspond to the intradelay of propagation inside the source and destination FPGA, respectively. During the intra-FPGA place and route tasks, we define a multicycle path constraint to set the intra-delay propagation to 3 times the intercommunication period; that is, in order to relax the timing constraint inside each FPGA.
The is the delay of the inter-FPGA communication. This delay should be reduced in order to optimize the system frequency.
The communication delay is represented by the following expression: is the amount of delay spent to transfer all signals via the same physical wire and it is proportional to the multiplexing ratio. The is the delay spent to cross all the routing hops. In fact, the number of routing hops is the number of FPGAs to cross to route a signal between the source and the destination. In order to reduce the multiplexing ratio, the effort should be spent on the routing task.
Indeed, using an appropriate routing algorithm, the router can find the optimized solution related to the given constraints. This parameter is calculated as the max of the multiplexing ratio of all the FPGA pairs. Figure 4 shows the proposed flow to reduce the multiplexing ratio. Otherwise, the router exits with the best obtained multiplexing ratio. One netlist is generated for each FPGA. Each netlist must be processed with FPGA specific automated place and route software to generate configuration bitstreams.
The techniques mentioned in Section 2 use constructive routing algorithm. This algorithm keeps the track of the reserved and available physical connections between FPGAs. If the shortest path exists, the capacity of all used resources is decremented; then, they cannot be used to route the next signals.
Otherwise, router returns unsuccessfully. The main disadvantage of this method is its irreversibility. Indeed, when a signal is already routed, it cannot be rerouted to leave the routing resources currently used to another signal that has the greatest need for these resources.
In the example of Figure 5 , signals are routed randomly. In this case, the design is considered nonroutable. To avoid this problem, we route the inter-FPGA signals by an iterative routing algorithm.
Among existing techniques, the Pathfinder routing algorithm seems to be best suited to our problem as it offers a compromise between performance and routability goals.
Figure 5: Conflict resolution by an iterative routing algorithm. Therefore, we chose to model all the routing resources by an oriented routing graph. The set of edges, , represents all the inter-FPGA connections. An unidirectional connection is modelled by a directed edge, while a bidirectional connection e. Figure 6 presents a routing graph of a three-FPGA-based platform.
We adapt it to deal with the inter-FPGA signals [ 21 ]. Pathfinder uses an iterative, negotiation-based approach to successfully route all the signals. The routing problem for a given signal is to find a directed tree embedded in that connects the source of the signal to each of its FPGA destinations.
During the first routing iteration, the signals are freely routed without paying attention to resource sharing. At the end of the first iteration, resources may be congested because multiple signals have used them. During subsequent iterations, the cost of using a resource is increased, based on the number of signals that share the resource and the history of congestion on that resource. Thus, signals are forced to negotiate for routing resources. If a resource is highly congested, nets which can use lower congestion alternatives are forced to do so.
On the other hand, if the alternatives are more congested than the resource, then a signal may still use that resource. Observing the final routing results, we notice that inter-FPGA signals can be directly routed between source and destination FPGAs or intermediate through-hops may be necessary.
Routing Algorithm Adaptation Taking into account some problems to be detailed later, we adapt our routing approach to the new routing topology.
In this section, we discuss the proposed solutions and the various changes we make. Signal with indirect direction is the signal which is directed towards the opposite. Signal Direction Conflicts The Pathfinder routing algorithm processes each signal independently.
Each routing resource node may be shared by more than one signal. Signals that share the same resource are multiplexed together.
As mentioned above, we model our architecture by a bidirectional routing graph. This causes direction conflicts since the signals sharing the same resources can have different directions.