Can Parallel Programming Revolutionize EDA Tools?

Concurrent CPU-GPU Task Programming using Modern C++

“…Figure 2 demonstrates a conventional VLSI CAD flow with a highlight on physical design. Due to the ever-increasing design complexity, the recent CAD community is driving the need for hybrid CPU-GPU computing to keep tool performance up with the technology scaling [14], [15]. Fig.…”

“…For example, a million-gate design can produce a graph of billions of tasks and dependencies that takes several days to accomplish [13]. However, such difficulty does not prevent CAD tools from parallelization, but highlights the need of new tasking frameworks to implement efficient parallel decomposition strategies especially with CPU-GPU collaborative computing [15].…”

“…Unfortunately, most parallel CPU-GPU programming solutions in CAD tools are hard-coded [14], [15]. Developers are "heroic programmers" to handcraft every detail of a heterogeneous decomposition algorithm and explicitly decide which part of the application runs on which CPU and GPU.…”

“…Under 40 cores, it takes 14.02s and 13.61s for 1 GPU and 4 GPUs, respectively. In fact, this property is generally true for most optimization algorithms in VLSI CAD, as they are often irregular and dependent [15]. In terms of different problem sizes which is measured by the iteration count used to construct the task graph, increasing the number of CPU cores can reduce the runtime in most scenarios.…”