This paper introduces McPAT, an integrated power, area, and timing modeling framework that supports comprehensive design space exploration for multicore and manycore processor configurations ranging from 90nm to 22nm and beyond. At the microarchitectural level, McPAT includes models for the fundamental components of a chip multiprocessor, including in-order and out-of-order processor cores, networks-on-chip, shared caches, integrated memory controllers, and multiple-domain clocking. At the circuit and technology levels, McPAT supports critical-path timing modeling, area modeling, and dynamic, short-circuit, and leakage power modeling for each of the device types forecast in the ITRS roadmap including bulk CMOS, SOI, and double-gate transistors. McPAT has a flexible XML interface to facilitate its use with many performance simulators. Combined with a performance simulator, McPAT enables architects to consistently quantify the cost of new ideas and assess tradeoffs of different architectures using new metrics like energy-delay-area2 product (EDA2P) and energy-delay-area product (EDAP). This paper explores the interconnect options of future manycore processors by varying the degree of clustering over generations of process technologies. Clustering will bring interesting tradeoffs between area and performance because the interconnects needed to group cores into clusters incur area overhead, but many applications can make good use of them due to synergies of cache sharing. Combining power, area, and timing results of McPAT with performance simulation of PARSEC benchmarks at the 22nm technology node for both common in-order and out-of-order manycore designs shows that when die cost is not taken into account clustering 8 cores together gives the best energy-delay product, whereas when cost is taken into account configuring clusters with 4 cores gives the best EDA2P and EDAP.

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McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures

This paper evaluates the suitability of the MapReduce model for multi-core and multi-processor systems. MapReduce was created by Google for application development on data-centers with thousands of servers. It allows programmers to write functional-style code that is automatically parallelized and scheduled in a distributed system. We describe Phoenix, an implementation of MapReduce for shared-memory systems that includes a programming API and an efficient runtime system. The Phoenix runtime automatically manages thread creation, dynamic task scheduling, data partitioning, and fault tolerance across processor nodes. We study Phoenix with multi-core and symmetric multiprocessor systems and evaluate its performance potential and error recovery features. We also compare MapReduce code to code written in lower-level APIs such as P-threads. Overall, we establish that, given a careful implementation, MapReduce is a promising model for scalable performance on shared-memory systems with simple parallel code

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Evaluating MapReduce for Multi-core and Multiprocessor Systems

Performance of deep-submicrometer very large scale integrated (VLSI) circuits is being increasingly dominated by the interconnects due to decreasing wire pitch and increasing die size. Additionally, heterogeneous integration of different technologies in one single chip is becoming increasingly desirable, for which planar (two-dimensional) ICs may not be suitable. This paper analyzes the limitations of the existing interconnect technologies and design methodologies and presents a novel three-dimensional (3-D) chip design strategy that exploits the vertical dimension to alleviate the interconnect related problems and to facilitate heterogeneous integration of technologies to realize a system-on-a-chip (SoC) design. A comprehensive analytical treatment of these 3-D ICs has been presented and it has been shown that by simply dividing a planar chip into separate blocks, each occurring a separate physical level interconnected by short and vertical interlayer interconnects (VILICs), significant improvement in performance and reduction in wire-limited chip area can be achieved, without the aid of any other circuit or design innovations. A scheme to optimize the interconnect distribution among different interconnect tiers is presented and the effect of transferring the repeaters to upper Si layers has been quantified in this analysis for a two-layer 3-D chip. Furthermore, one of the major concerns in 3-D ICs arising due to power dissipation problems has been analyzed and an analytical model has been presented to estimate the temperatures of the different active layers. It is demonstrated that advancement in heat sinking technology will be necessary in order to extract maximum performance from these chips. Implications of 3-D device architecture on several design issues have also been discussed with special attention to SoC design strategies. Finally some of the promising technologies for manufacturing 3-D ICs have been outlined.

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3-D ICs: a novel chip design for improving deep-submicrometer interconnect performance and systems-on-chip integration

The Niagara processor implements a thread-rich architecture designed to provide a high-performance solution for commercial server applications. This is an entirely new implementation of the Sparc V9 architectural specification, which exploits large amounts of on-chip parallelism to provide high throughput. The hardware supports 32 threads with a memory subsystem consisting of an on-board crossbar, level-2 cache, and memory controllers for a highly integrated design that exploits the thread-level parallelism inherent to server applications, while targeting low levels of power consumption.

Niagara: a 32-way multithreaded Sparc processor

Commodity computer systems contain more and more processor cores and exhibit increasingly diverse architectural tradeoffs, including memory hierarchies, interconnects, instruction sets and variants, and IO configurations. Previous high-performance computing systems have scaled in specific cases, but the dynamic nature of modern client and server workloads, coupled with the impossibility of statically optimizing an OS for all workloads and hardware variants pose serious challenges for operating system structures.We argue that the challenge of future multicore hardware is best met by embracing the networked nature of the machine, rethinking OS architecture using ideas from distributed systems. We investigate a new OS structure, the multikernel, that treats the machine as a network of independent cores, assumes no inter-core sharing at the lowest level, and moves traditional OS functionality to a distributed system of processes that communicate via message-passing.We have implemented a multikernel OS to show that the approach is promising, and we describe how traditional scalability problems for operating systems (such as memory management) can be effectively recast using messages and can exploit insights from distributed systems and networking. An evaluation of our prototype on multicore systems shows that, even on present-day machines, the performance of a multikernel is comparable with a conventional OS, and can scale better to support future hardware.

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The multikernel: a new OS architecture for scalable multicore systems

This first generation of "Niagara" SPARC processors implements a power-efficient Chip Multi-Threading (CMT) architecture which maximizes overall throughput performance for commercial workloads. The target performance is achieved by exploiting high bandwidth rather than high frequency, thereby reducing hardware complexity and power. The UltraSPARC T1 processor combines eight four-threaded 64-b cores, a floating-point unit, a high-bandwidth interconnect crossbar, a shared 3-MB L2 Cache, four DDR2 DRAM interfaces, and a system interface unit. Power and thermal monitoring techniques further enhance CMT performance benefits, increasing overall chip reliability. The 378-mm2 die is fabricated in Texas Instrument's 90-nm CMOS technology with nine layers of copper interconnect. The chip contains 279 million transistors and consumes a maximum of 63 W at 1.2 GHz and 1.2 V. Key functional units employ special circuit techniques to provide the high bandwidth required by a CMT architecture while optimizing power and silicon area. These include a highly integrated integer register file, a high-bandwidth interconnect crossbar, the shared L2 cache, and the IO subsystem. Key aspects of the physical design methodology are also discussed

A Power-Efficient High-Throughput 32-Thread SPARC Processor

This is a second-generation, highly-integrated superscalar processor implementing the Sparc V9 64b architecture. Performance is improved by increasing clock frequency and by improvements in the memory system. Clock rates up to 330 MHz are achieved. Microarchitecture improvements include a pre-fetch instruction, multiple outstanding block loads and stores, and support for a wide range of cache sizes and system frequencies. These result in improved computation, multimedia, and networking performance. This design is implemented on a 5-metal-layer, 0.35 /spl mu/m process.

P. Kongetira

Papers

Niagara: a 32-way multithreaded Sparc processor

A Power-Efficient High-Throughput 32-Thread SPARC Processor

A 330 MHz 4-way superscalar microprocessor