Using MCD-DVS for dynamic thermal management performance improvement

With chip temperature being a major hurdle in microprocessor design, techniques to recover the performance loss due to thermal emergency mechanisms are crucial in order to sustain performance growth. Many techniques for power reduction in the past and some on thermal management more recently have contributed to alleviate this problem. Probably the most important thermal control technique is dynamic voltage and frequency scaling (DVS) which allows for almost cubic reduction in power with worst-case performance penalty only linear. So far, DVS techniques for temperature control have been studied at the chip level. Finer grain DVS is feasible if a globally-asynchronous locally-synchronous (GALS) design style is employed. GALS, also known as multiple-clock domain (MCD), allows for an independent voltage and frequency control for each one of the clock domains that are part of the chip. There are several studies on DVS for GALS that aim to improve energy and power efficiency but not temperature. This paper proposes and analyses the usage of DVS at the domain level to control temperature in a clustered MCD microarchitecture with the goal of improving the performance of applications that do not meet the thermal constraints imposed by the designers.Peer ReviewedPostprint (published version

Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnections

Cortical synapse organization supports a range of dynamic states on multiple spatial and temporal scales, from synchronous slow wave activity (SWA), characteristic of deep sleep or anesthesia, to fluctuating, asynchronous activity during wakefulness (AW). Such dynamic diversity poses a challenge for producing efficient large-scale simulations that embody realistic metaphors of short- and long-range synaptic connectivity. In fact, during SWA and AW different spatial extents of the cortical tissue are active in a given timespan and at different firing rates, which implies a wide variety of loads of local computation and communication. A balanced evaluation of simulation performance and robustness should therefore include tests of a variety of cortical dynamic states. Here, we demonstrate performance scaling of our proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and AW for bidimensional grids of neural populations, which reflects the modular organization of the cortex. We explored networks up to 192x192 modules, each composed of 1250 integrate-and-fire neurons with spike-frequency adaptation, and exponentially decaying inter-modular synaptic connectivity with varying spatial decay constant. For the largest networks the total number of synapses was over 70 billion. The execution platform included up to 64 dual-socket nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40GHz clock rates. Network initialization time, memory usage, and execution time showed good scaling performances from 1 to 1024 processes, implemented using the standard Message Passing Interface (MPI) protocol. We achieved simulation speeds of between 2.3x10^9 and 4.1x10^9 synaptic events per second for both cortical states in the explored range of inter-modular interconnections.Comment: 22 pages, 9 figures, 4 table

Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnections

Cortical synapse organization supports a range of dynamic states on multiple spatial and temporal scales, from synchronous slow wave activity (SWA), characteristic of deep sleep or anesthesia, to fluctuating, asynchronous activity during wakefulness (AW). Such dynamic diversity poses a challenge for producing efficient large-scale simulations that embody realistic metaphors of short- and long-range synaptic connectivity. In fact, during SWA and AW different spatial extents of the cortical tissue are active in a given timespan and at different firing rates, which implies a wide variety of loads of local computation and communication. A balanced evaluation of simulation performance and robustness should therefore include tests of a variety of cortical dynamic states. Here, we demonstrate performance scaling of our proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and AW for bidimensional grids of neural populations, which reflects the modular organization of the cortex. We explored networks up to 192x192 modules, each composed of 1250 integrate-and-fire neurons with spike-frequency adaptation, and exponentially decaying inter-modular synaptic connectivity with varying spatial decay constant. For the largest networks the total number of synapses was over 70 billion. The execution platform included up to 64 dual-socket nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40GHz clock rates. Network initialization time, memory usage, and execution time showed good scaling performances from 1 to 1024 processes, implemented using the standard Message Passing Interface (MPI) protocol. We achieved simulation speeds of between 2.3x10^9 and 4.1x10^9 synaptic events per second for both cortical states in the explored range of inter-modular interconnections.Comment: 22 pages, 9 figures, 4 table

RAPPID: an asynchronous instruction length decoder

Journal ArticleThis paper describes an investigation of potential advantages and risks of applying an aggressive asynchronous design methodology to Intel Architecture. RAPPID ("Revolving Asynchronous Pentium® Processor Instruction Decoder"), a prototype IA32 instruction length decoding and steering unit, was implemented using self-timed techniques. RAPPID chip was fabricated on a 0.25m CMOS process and tested successfully. Results show significant advantages-in particular, performance of 2.5-4.5 instructions/nS-with manageable risks using this design technology. RAPPID achieves three times the throughput and half the latency, dissipating only half the power and requiring about the same area as an existing 400MHz clocked circuit

RAPPID: an asynchronous instruction length decoder

Journal ArticleThis paper describes an investigation of potential advantages and risks of applying an aggressive asynchronous design methodology to Intel Architecture. RAPPID ("Revolving Asynchronous Pentium® Processor Instruction Decoder"), a prototype IA32 instruction length decoding and steering unit, was implemented using self-timed techniques. RAPPID chip was fabricated on a 0.25m CMOS process and tested successfully. Results show significant advantages-in particular, performance of 2.5-4.5 instructions/nS-with manageable risks using this design technology. RAPPID achieves three times the throughput and half the latency, dissipating only half the power and requiring about the same area as an existing 400MHz clocked circuit

Doctor of Philosophy

dissertationCommunication surpasses computation as the power and performance bottleneck in forthcoming exascale processors. Scaling has made transistors cheap, but on-chip wires have grown more expensive, both in terms of latency as well as energy. Therefore, the need for low energy, high performance interconnects is highly pronounced, especially for long distance communication. In this work, we examine two aspects of the global signaling problem. The first part of the thesis focuses on a high bandwidth asynchronous signaling protocol for long distance communication. Asynchrony among intellectual property (IP) cores on a chip has become necessary in a System on Chip (SoC) environment. Traditional asynchronous handshaking protocol suffers from loss of throughput due to the added latency of sending the acknowledge signal back to the sender. We demonstrate a method that supports end-to-end communication across links with arbitrarily large latency, without limiting the bandwidth, so long as line variation can be reliably controlled. We also evaluate the energy and latency improvements as a result of the design choices made available by this protocol. The use of transmission lines as a physical interconnect medium shows promise for deep submicron technologies. In our evaluations, we notice a lower energy footprint, as well as vastly reduced wire latency for transmission line interconnects. We approach this problem from two sides. Using field solvers, we investigate the physical design choices to determine the optimal way to implement these lines for a given back-end-of-line (BEOL) stack. We also approach the problem from a system designer's viewpoint, looking at ways to optimize the lines for different performance targets. This work analyzes the advantages and pitfalls of implementing asynchronous channel protocols for communication over long distances. Finally, the innovations resulting from this work are applied to a network-on-chip design example and the resulting power-performance benefits are reported

An asynchronous instruction length decoder

Journal ArticleAbstract-This paper describes an investigation of potential advantages and pitfalls of applying an asynchronous design methodology to an advanced microprocessor architecture. A prototype complex instruction set length decoding and steering unit was implemented using self-timed circuits. [The Revolving Asynchronous Pentium® Processor Instruction Decoder (RAPPID) design implemented the complete Pentium II® 32-bit MMX instruction set.] The prototype chip was fabricated on a 0.25-CMOS process and tested successfully. Results show significant advantages-in particular, performance of 2.5-4.5 instructions per nanosecond-with manageable risks using this design technology. The prototype achieves three times the throughput and half the latency, dissipating only half the power and requiring about the same area as the fastest commercial 400-MHz clocked circuit fabricated on the same process

Comparing energy and latency of asynchronous and synchronous NoCs for embedded SoCs

Journal ArticlePower consumption of on-chip interconnects is a primary concern for many embedded system-on-chip (SoC) applications. In this paper, we compare energy and performance characteristics of asynchronous (clockless) and synchronous network on-chip implementations, optimized for a number of SoC designs. We adapted the COSI-2.0 framework with ORION 2.0 router and wire models for synchronous network generation. Our own tool, ANetGen, specifies the asynchronous network by determining the topology with simulated-annealing and router locations with force-directed placement. It uses energy and delay models from our 65 nm bundled-data router design. SystemC simulations varied traffic burstiness using the self-similar b-model. Results show that the asynchronous network provided lower median and maximum message latency, especially under bursty traffic, and used far less router energy with a slight overhead for the interrouter wires