A performance model of multicast communication in wormhole-routed networks on-chip

Collective communication operations form a part of overall traffic in most applications running on platforms employing direct interconnection networks. This paper presents a novel analytical model to compute communication latency of multicast as a widely used collective communication operation. The novelty of the model lies in its ability to predict the latency of the multicast communication in wormhole-routed architectures employing asynchronous multi-port routers scheme. The model is applied to the Quarc NoC and its validity is verified by comparing the model predictions against the results obtained from a discrete-event simulator developed using OMNET++

A communication model of broadcast in wormhole-routed networks on-chip

This paper presents a novel analytical model to compute communication latency of broadcast as the most fundamental collective communication operation. The novelty of the model lies in its ability to predict the broadcast communication latency in wormhole-routed architectures employing asynchronous multi-port routers scheme. The model is applied to the Quarc NoC and its validity is verified by comparing the model predictions against the results obtained from a discrete-event simulator developed using OMNET++

An analytical performance model for the Spidergon NoC

Networks on chip (NoC) emerged as a promising alternative to bus-based interconnect networks to handle the increasing communication requirements of the large systems on chip. Employing an appropriate topology for a NoC is of high importance mainly because it typically trade-offs between cross-cutting concerns such as performance and cost. The spidergon topology is a novel architecture which is proposed recently for NoC domain. The objective of the spidergon NoC has been addressing the need for a fixed and optimized topology to realize cost effective multi-processor SoC (MPSoC) development [7]. In this paper we analyze the traffic behavior in the spidergon scheme and present an analytical evaluation of the average message latency in the architecture. We prove the validity of the analysis by comparing the model against the results produced by a discreteevent simulator

Power aware early design stage hardware software co-optimization

Co-optimizing hardware and software can lead to substantial performance and energy benefits, and is becoming an increasingly important design paradigm. In scientific computing, power constraints increasingly necessitate the return to specialized chips such as Intel’s MIC or IBM’s Blue-Gene architectures. To enable hardware/software co-design in early stages of the design cycle, we propose a simulation infrastructure methodology by combining high-abstraction performance simulation using Sniper with power modeling using McPAT and custom DRAM power models. Sniper/McPAT is fast — simulation speed is around 2 MIPS on an 8-core host machine — because it uses analytical modeling to abstract away core performance during multi-core simulation. We demonstrate Sniper/McPAT’s accuracy through validation against real hardware; we report average performance and power prediction errors of 22.1% and 8.3%, respectively, for a set of SPEComp benchmarks

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Interval simulation: raising the level of abstraction in architectural simulation

Detailed architectural simulators suffer from a long development cycle and extremely long evaluation times. This longstanding problem is further exacerbated in the multi-core processor era. Existing solutions address the simulation problem by either sampling the simulated instruction stream or by mapping the simulation models on FPGAs; these approaches achieve substantial simulation speedups while simulating performance in a cycle-accurate manner This paper proposes interval simulation which rakes a completely different approach: interval simulation raises the level of abstraction and replaces the core-level cycle-accurate simulation model by a mechanistic analytical model. The analytical model estimates core-level performance by analyzing intervals, or the timing between two miss events (branch mispredictions and TLB/cache misses); the miss events are determined through simulation of the memory hierarchy, cache coherence protocol, interconnection network and branch predictor By raising the level of abstraction, interval simulation reduces both development time and evaluation time. Our experimental results using the SPEC CPU2000 and PARSEC benchmark suites and the MS multi-core simulator show good accuracy up to eight cores (average error of 4.6% and max error of 11% for the multi-threaded full-system workloads), while achieving a one order of magnitude simulation speedup compared to cycle-accurate simulation. Moreover interval simulation is easy to implement: our implementation of the mechanistic analytical model incurs only one thousand lines of code. Its high accuracy, fast simulation speed and ease-of-use make interval simulation a useful complement to the architect's toolbox for exploring system-level and high-level micro-architecture trade-offs

Iso-energy-efficiency: An approach to power-constrained parallel computation

Future large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance of data intensive parallel applications with various execution patterns running on large scale power-aware clusters. Our analytical model can help users explore the effects of machine and application dependent characteristics on system energy efficiency and isolate efficient ways to scale system parameters (e.g. processor count, CPU power/frequency, workload size and network bandwidth) to balance energy use and performance. We derive our iso-energy-efficiency model and apply it to the NAS Parallel Benchmarks on two power-aware clusters. Our results indicate that the model accurately predicts total system energy consumption within 5% error on average for parallel applications with various execution and communication patterns. We demonstrate effective use of the model for various application contexts and in scalability decision-making

Modeling Solder Ball Array Interconnects for Power Module Optimization

PowerSynth is a software platform that can co-optimize power modules utilizing a 2D topology and wire bond interconnects. The novel 3D architectures being proposed at the University of Arkansas utilize solder ball interconnects instead of wire bonds. Therefore, they currently cannot be optimized using PowerSynth. This paper examines methods to accurately model the parasitic inductance of solder balls and ball grid arrays so they may be implemented into software for optimization. Proposed mathematical models are validated against ANSYS Electromagnetics Suite simulations. A comparison of the simulated data shows that mathematical models are well suited for implementation into optimization software platforms. Experimental measurements proved to be inconclusive and necessitate future work