Scaling of CMOS feature size has long been a source of dramatic performance gains. However, the reduction in voltage levels has not been able to match this rate of scaling, leading to increasing operating temperatures and current densities. Given that most wearout mechanisms that plague semiconductor devices are highly dependent on these parameters, significantly higher failure rates are projected for future technology generations. Consequently, high reliability and fault tolerance, which have traditionally been subjects of interest for high-end server markets, are now getting emphasis in the mainstream desktop and embedded systems space. The popular solution for this has been the use of redundancy at a coarse granularity, such as dual/triple modular redundancy. In this work, we challenge the practice of coarse-granularity redundancy by identifying its inability to scale to high failure rate scenarios and investigating the advantages of finer-grained configurations. To this end, this paper presents and evaluates a highly reconfigurable multicore architecture, named StageNet (SN), that is designed with reliability as its first class design criteria. SN relies on a reconfigurable network of replicated processor pipeline stages to maximize the useful lifetime of a chip, gracefully degrading performance towards the end of life. Our results show that the proposed SN architecture can perform nearly 50% more cumulative work compared to a traditional multicore.
Technology scaling has delivered on its promises of increasing device density on a single chip. However, the voltage scaling trend has failed to keep up, introducing tight power constraints on manufactured parts. In such a scenario, there is a need to incorporate energy-efficient processing resources that can enable more computation within the same power budget. Energy efficiency solutions in the past have typically relied on application specific hardware and accelerators. Unfortunately, these approaches do not extend to general purpose applications due to their irregular and diverse code base. Towards this end, we propose BERET, an energy-efficient co-processor that can be configured to benefit a wide range of applications. Our approach identifies recurring instruction sequences as phases of "temporal regularity" in a program's execution, and maps suitable ones to the BERET hardware, a three-stage pipeline with a bundled execution model. This judicious off-loading of program execution to a reduced-complexity hardware demonstrates significant savings on instruction fetch, decode and register file accesses energy. On average, BERET reduces energy consumption by a factor of 3-4X for the program regions selected across a range of general-purpose and media applications. The average energy savings for the entire application run was 35% over a single-issue in-order processor.
Technology scaling, characterized by decreasing feature size, thinning gate oxide, and non-ideal voltage scaling, will become a major hindrance to microprocessor reliability in future technology generations. Physical analysis of device failure mechanisms has shown that most wearout mechanisms projected to plague future technology generations are progressive, meaning that the circuit-level effects of wearout develop and intensify with age over the lifetime of the chip. This work leverages the progression of wearout over time in order to present a low-cost hardware structure that identifies increasing propagation delay, which is symptomatic of many forms of wearout, to accurately forecast the failure of microarchitectural structures. To motivate the use of this predictive technique, an HSPICE analysis of the effects of one particular failure mechanism, gate oxide breakdown, on gates from a standard cell library characterized for a 90 nm process is presented. This gate-level analysis is then used to demonstrate the aggregate change in output delay of high-level structures within a synthesized Verilog model of an embedded microprocessor core. Leveraging this analysis, a selfcalibrating hardware structure for conducting statistical analysis of output delay is presented and its efficacy in predicting the failure of a variety of structures within the microprocessor core is evaluated.
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