@article{poss13micpro,
	Abstract = {To harness the potential of CMPs for scalable, energy-efficient performance in general-purpose computers, the Apple-CORE project has co-designed a general machine model and concurrency control interface with dedicated hardware support for concurrency management across multiple cores. Its SVP interface combines dataflow synchronisation with imperative programming, towards the efficient use of parallelism in general-purpose workloads. Its implementation in hardware provides logic able to coordinate single-issue, in-order multi-threaded RISC cores into computation clusters on chip, called Microgrids. In contrast with the traditional ``accelerator'' approach, Microgrids are components in distributed systems on chip that consider both clusters of small cores and optional, larger sequential cores as system services shared between applications. The key aspects of the design are asynchrony, i.e. the ability to tolerate irregular long latencies on chip, a scale-invariant programming model, a distributed chip resource model, and the transparent performance scaling of a single program binary code across multiple cluster sizes. This article describes the execution model, the core micro-architecture, its realization in a many-core, general-purpose processor chip and its software environment. This article also presents cycle-accurate simulation results for various key algorithmic and cryptographic kernels. The results show good efficiency in terms of the utilisation of hardware despite the high-latency memory accesses and good scalability across relatively large clusters of cores.},
	Author = {Raphael Poss and Mike Lankamp and Qiang Yang and Jian Fu and Michiel W. {van Tol} and Irfan Uddin and Chris Jesshope},


	Doi = {10.1016/j.micpro.2013.05.004}, Urldoi = {http://dx.doi.org/10.1016/j.micpro.2013.05.004},
	Issn = {0141-9331},
	Journal = {Microprocessors and Microsystems},
	Month = {November},
	Number = {8},
	Pages = {1090--1101},
	Read = {1},
	Title = {{Apple-CORE}: harnessing general-purpose many-cores with hardware concurrency management},
	Urllocal = {pub/poss.13.micpro.pdf},
	Volume = {37},
	Year = {2013},
	
	}

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Its SVP interface combines dataflow synchronisation with imperative programming, towards the efficient use of parallelism in general-purpose workloads. Its implementation in hardware provides logic able to coordinate single-issue, in-order multi-threaded RISC cores into computation clusters on chip, called Microgrids. In contrast with the traditional ``accelerator'' approach, Microgrids are components in distributed systems on chip that consider both clusters of small cores and optional, larger sequential cores as system services shared between applications. The key aspects of the design are asynchrony, i.e. the ability to tolerate irregular long latencies on chip, a scale-invariant programming model, a distributed chip resource model, and the transparent performance scaling of a single program binary code across multiple cluster sizes. This article describes the execution model, the core micro-architecture, its realization in a many-core, general-purpose processor chip and its software environment. This article also presents cycle-accurate simulation results for various key algorithmic and cryptographic kernels. 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Its SVP interface combines dataflow synchronisation with imperative programming, towards the efficient use of parallelism in general-purpose workloads. Its implementation in hardware provides logic able to coordinate single-issue, in-order multi-threaded RISC cores into computation clusters on chip, called Microgrids. In contrast with the traditional ``accelerator'' approach, Microgrids are components in distributed systems on chip that consider both clusters of small cores and optional, larger sequential cores as system services shared between applications. The key aspects of the design are asynchrony, i.e. the ability to tolerate irregular long latencies on chip, a scale-invariant programming model, a distributed chip resource model, and the transparent performance scaling of a single program binary code across multiple cluster sizes. This article describes the execution model, the core micro-architecture, its realization in a many-core, general-purpose processor chip and its software environment. This article also presents cycle-accurate simulation results for various key algorithmic and cryptographic kernels. 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