Heterogeneous systems on chip (HeSoCs) co-integrate a high-performance multicore host processor with programmable manycore accelerators (PMCAs) to combine "standard platform" software support (e.g. the Linux OS) with energy-efficient, domain-specific, highly parallel processing capabilities.In this work, we present HERO, a HeSoC platform that tackles this challenge in a novel way. HERO's host processor is an industry-standard ARM Cortex-A multicore complex, while its PMCA is a scalable, silicon-proven, open-source many-core processing engine, based on the extensible, open RISC-V ISA.We evaluate a prototype implementation of HERO, where the PMCA implemented on an FPGA fabric is coupled with a hard ARM Cortex-A host processor, and show that the run time overhead compared to manually written PMCA code operating on private physical memory is lower than 10 % for pivotal benchmarks and operating conditions.
Kurth A., Capotondi A., Vogel P., Benini L., Marongiu A. (2018). Hero: An open-source research platform for HW/SW exploration of heterogeneous manycore systems. 1515 BROADWAY, NEW YORK, NY 10036-9998 USA : Association for Computing Machinery [10.1145/3295816.3295821].
Hero: An open-source research platform for HW/SW exploration of heterogeneous manycore systems
Capotondi A.
;Benini L.;Marongiu A.
2018
Abstract
Heterogeneous systems on chip (HeSoCs) co-integrate a high-performance multicore host processor with programmable manycore accelerators (PMCAs) to combine "standard platform" software support (e.g. the Linux OS) with energy-efficient, domain-specific, highly parallel processing capabilities.In this work, we present HERO, a HeSoC platform that tackles this challenge in a novel way. HERO's host processor is an industry-standard ARM Cortex-A multicore complex, while its PMCA is a scalable, silicon-proven, open-source many-core processing engine, based on the extensible, open RISC-V ISA.We evaluate a prototype implementation of HERO, where the PMCA implemented on an FPGA fabric is coupled with a hard ARM Cortex-A host processor, and show that the run time overhead compared to manually written PMCA code operating on private physical memory is lower than 10 % for pivotal benchmarks and operating conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.