Cyberphysical systems have numerous industrial and commercial applications. Such systems are often built using low-resource devices that gather and process data, using machine-learning (ML) models, to make intelligent decisions and provide value to users. Programming such low-resource devices with an impoverished system runtime is often challenging.<\/p>\n
This paper presents a new domain-specific language called PiCon for programming ML pipelines in low-resource devices. PiCon allows safe I\/O-compute concurrency, ruling out a large class of errors, while providing a simple and sequential coding abstraction to the programmer. PiCon compiles to C code and easily interfaces with existing C\/C++ code. Furthermore, the generated code does not rely on multi-threading support or dynamic memory allocation, dramatically reducing its footprint on the device. We present experience porting two real-world ML applications that demonstrate simplification in programmability, in addition to several safe-by-construction guarantees<\/p>\n","protected":false},"excerpt":{"rendered":"
Cyberphysical systems have numerous industrial and commercial applications. Such systems are often built using low-resource devices that gather and process data, using machine-learning (ML) models, to make intelligent decisions and provide value to users. Programming such low-resource devices with an impoverished system runtime is often challenging. This paper presents a new domain-specific language called PiCon 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