An Heterogeneous Compiler Of Dataflow Programs For Zynq Platforms
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High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...
A central task in high-level synthesis is scheduling: the allocation of operations to clock cycles. The classic approach to scheduling is static, in which each operation is mapped to a clock cycle at compile-time, but recent years have seen the emergence o ...
In High-Level Synthesis (HLS), we consider abstractions that span from software to hardware and target heterogeneous architectures. Therefore, managing the complexity introduced by this is key to implementing good, maintainable, and extendible HLS compiler ...
Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...
SPRINGER2023
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To achieve resource-efficient hardware designs, high-level synthesis (HLS) tools share (i.e., time-multiplex) functional units among operations of the same type. This optimization is typically performed in conjunction with operation scheduling to ensure th ...
New York2023
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Dataflow circuits promise to overcome the scheduling limitations of standard HLS solutions. However, their performance suffers due to timing overheads caused by their handshake communication protocol. Current pipelining solutions fail to account for logic ...
New York2023
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Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...
2022
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Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...
IEEE2022
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Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...
The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...