摘要:
Customisable embedded processors that are available on the market make it possible for designers to speed up execution of applications by using Application-specific Functional Units (AFUs), implementing Instruction-Set Extensions (ISEs). Furthermore, techniques for automatic ISE identification have been improving; many algorithms have been proposed for choosing, given the application's source code, the best ISEs under various constraints. Read and write ports between the AFUs and the processor register file are an expensive asset, fixed in the micro-architecture—some processors indeed only allow two read ports and one write port—and yet, on the other hand, a large availability of inputs and outputs to and from the AFUs exposes high speedup. Here we present a solution to the limitation of actual register file ports by serialising register file access and therefore addressing multi-cycle read and write. It does so in an innovative way for two reasons: (1) it exploits and brings forward the progress in ISE identification under constraint, and (2) it combines register file access serialisation with pipelining in order to obtain the best global solution. Our method consists of scheduling graphs—corresponding to ISEs—under input/output constraint
摘要:
Commercial data processors are available that include a capability of extending their instruction set for a specified application, i.e. of introducing customized functional units in the interest of enhanced processing performance. For such processors there is a need for automatically forming the extensions from high-level application code. A technique is described for selecting maximal-speedup convex subgraphs of the application dataflow graph under micro-architectural constraints.
摘要:
Reconfigurable Systems-an-Chip (RSoCs) on the market consist of full-fledged processors and large Field-Programmable Gate Arrays (FPGAs). The latter can be used to implement the system glue logic, various peripherals, and application-specific coprocessors. Using FPGAs for application-specific coprocessors has certain speedup potentials, but it is less present in practice because of the complexity of interfacing the software application with the coprocessor. In the present application, we present a virtualisation layer consisting of an operating system extension and a hardware component. It lowers the complexity of interfacing and increases portability potentials, while it also allows the coprocessor to access the user virtual memory through a virtual memory window. The burden of moving data between processor and coprocessor is shifted from the programmer to the operating system.
摘要:
Instruction Set Extensions (ISEs) can be used effectively to accelerate the performance of embedded processors. The critical, and difficult task of ISE selection is often performed manually by designers. A few automatic methods for ISE generation have shown good capabilities, but are still limited in the handling of memory accesses, and so they fail to directly address the memory wall problem.We present here the first ISE identification technique that can automatically identify state-holding Application-specific Functional Units (AFUs) comprehensively, thus being able to eliminate a large portion of memory traffic from cache and main memory. Our cycle-accurate results obtained by the SimpleScalar simulator show that the identified AFUs with architecturally visible storage gain significantly more than previous techniques, and achieve an average speedup of 2.8× over pure software execution. Moreover, the number of required memory-access instructions is reduced by two thirds on average, suggesting corresponding benefits on energy consumption.
摘要:
Instruction Set Extensions (ISEs) can be used effectively to accelerate the performance of embedded processors. The critical, and difficult task of ISE selection is often performed manually by designers. A few automatic methods for ISE generation have shown good capabilities, but are still limited in the handling of memory accesses, and so they fail to directly address the memory wall problem. We present here the first ISE identification technique that can automatically identify state-holding Application-specific Functional Units (AFUs) comprehensively, thus being able to eliminate a large portion of memory traffic from cache and main memory. Our cycle-accurate results obtained by the SimpleScalar simulator show that the identified AFUs with architecturally visible storage gain significantly more than previous techniques, and achieve an average speedup of 2.8× over pure software execution. Moreover, the number of required memory-access instructions is reduced by two thirds on average, suggesting corresponding benefits on energy consumption.
摘要:
Reconfigurable Systems-an-Chip (RSoCs) on the market consist of full-fledged processors and large Field-Programmable Gate Arrays (FPGAs). The latter can be used to implement the system glue logic, various peripherals, and application-specific coprocessors. Using FPGAs for application-specific coprocessors has certain speedup potentials, but it is less present in practice because of the complexity of interfacing the software application with the coprocessor. In the present application, we present a virtualisation layer consisting of an operating system extension and a hardware component. It lowers the complexity of interfacing and increases portability potentials, while it also allows the coprocessor to access the user virtual memory through a virtual memory window. The burden of moving data between processor and coprocessor is shifted from the programmer to the operating system.
摘要:
Commercial data processors are available that include a capability of extending their instruction set for a specified application, i.e. of introducing customized functional units in the interest of enhanced processing performance. For such processors there is a need for automatically forming the extensions from high-level application code. A technique is described for selecting maximal-speedup convex subgraphs of the application dataflow graph under micro-architectural constraints.