52 research outputs found
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Dynamic Processor Reconfiguration for Power, Performance and Reliability Management
Technology advancements allowed more transistors to be packed in a smaller area, while the improved performance helped in achieving higher clock frequencies. This, unfortunately led to a power density problem, forcing processor industry to lower the clock frequency and integrate multiple cores on the same die. Depending on core characteristics, the multiple cores in the die could be symmetric or asymmetric. Asymmetric multi-core processors (AMPs) have been proposed as an alternative to symmetric multi-cores to improve power efficiency. AMPs comprise of cores that implement the same ISA, but differ in performance and power characteristics due to varying sizes of micro-architectural resources. As the computational bottleneck of a workload shifts from one resource to another during its course of execution, reassigning it to another core (where it runs more efficiently), can improve the overall power efficiency. Thus achieving high power efficiency in AMPs requires (i) a diverse set of cores that are optimized for various program phases, (ii) runtime analysis to determine the best core to run on, and (iii) low overhead of re-assigning a thread to a different core type.
Decisions to swap threads between AMPs are made at coarse grain granularity of millions of instructions, to mitigate the impact of thread migration overhead. But the computational needs of the program rapidly change during the course of its execution. The best core configuration for an application such that, both power consumption and performance are optimized, changes over time rapidly at fine granularity of thousands of instructions. This dissertation explores ways to design core micro-architecture such that high power efficiency could be achieved, if switching overhead could be lowered, enabling fine grain switching.
To take advantage of power saving opportunities at fine grain granularity, this thesis explores reconfigurable/morphable architectures where core resources are reconfigured on demand to suit the needs of the executing application. At first, we explore reconfigurable architectures consisting of two kinds of cores: out-of-order (OOO) big cores and in-order (InO) small cores. The big cores provide higher performance while the small cores are more power efficient. In this proposed architecture, OOO core reconfigures into InO core at run time. Our proposed online management scheme decides to switch between these core types such that we obtain significant power benefits without impacting performance. We also observe that, resource requirements of applications can be quite diverse and consequently, resource bottlenecks or excesses can vary considerably. Thus, reconfiguration between just two core modes may not fully exploit power and performance improvement opportunities.
We therefore, explore reconfigurable architectures consisting of diverse core types that not limited to big and little cores. A single core can reconfigure into multiple core modes where each mode has unique power and performance characteristics. Workload performance on a particular core mode depends on a large set of processor resources. Some workloads are highly memory intensive, some exhibit large instruction dependency, some experience high rates of branch mis-prediction, while other workloads exhibit large exploitable instruction level parallelism. A diverse set of core modes is needed, that could address shifting resource needs during various program phases of an application. Different trade-offs in power and performance could be achieved by reducing or expanding the size of various resource. Trade-offs for each core mode are also affected by operating voltage and frequency. We therefore, propose joint core resource resizing with dynamic voltage and frequency scaling (DVFS), which is important for applications whose performance is sensitive to changes in frequency. Thus, at fine granularity, the core should adapt to varying instruction window sizes, execution bandwidth and frequency to meet the demands of the workload at run-time to improve power efficiency.
Many current processors employ DVFS aggressively to improve power efficiency and maximize performance. This dissertation studies the tradeoff in power efficiency in using fine grain DVFS and reconfigurable architectures mentioned above.We also explore another important problem due to continued scaling of devices which results in higher vulnerability to soft-errors. We consider dynamic core reconfiguration from the perspectives of both power efficiency and vulnerability to soft-errors. An online management scheme is proposed such that core reconfiguration upon a thread switch not only improves power efficiency but also does not increase the vulnerability to soft errors.
In summary, we propose in this thesis several solutions for improving power efficiency by integrating heterogeneity within the core. We also address how popular power reduction techniques like DVFS are comparable to our approach. Finally, we address reliability challenges along with improving power efficiency
Four Metrics to Evaluate Heterogeneous Multicores
Semiconductor device scaling has made single-ISA heterogeneous processors a reality. Heterogeneous processors contain a number of different CPU cores that all implement the same Instruction Set Architecture (ISA). This enables greater flexibility and specialization, as runtime constraints and workload characteristics can influence which core a given workload is run on. A major roadblock to the further development of heterogeneous processors is the lack of appropriate evaluation metrics. Existing metrics can be used to evaluate individual cores, but to evaluate a heterogeneous processor, the cores must be considered as a collective. Without appropriate metrics, it is impossible to establish design goals for processors, and it is difficult to accurately compare two different heterogeneous processors.
We present four new metrics to evaluate user-oriented aspects of sets of heterogeneous cores:
localized nonuniformity
,
gap overhead
,
set overhead
, and
generality
. The metrics consider sets rather than individual cores. We use examples to demonstrate each metric, and show that the metrics can be used to quantify intuitions about heterogeneous cores.
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DynaMOS: Dynamic Schedule Migration for Heterogeneous Cores
ABSTRACT InOrder (InO) cores achieve limited performance because their inability to dynamically reorder instructions prevents them from exploiting Instruction-Level-Parallelism. Conversely, Out-of-Order (OoO) cores achieve high performance by aggressively speculating past stalled instructions and creating highly optimized issue schedules. It has been observed that these issue schedules tend to repeat for sequences of instructions with predictable control and data-flow. An equally provisioned InO core can potentially achieve OoO's performance at a fraction of the energy cost if provided with an OoO schedule. In the context of a fine-grained heterogeneous multicore system composed of a big (OoO) core and a little (InO) core, we could offload recurring issue schedules from the big to the little core, to achieve energyefficiency while maintaining performance. To this end, we introduce the DynaMOS architecture. Recurring issue schedules may contain instructions that speculate across branches, utilize renamed registers to eliminate false dependencies, and reorder memory operations. DynaMOS provisions little with an OinO mode to replay a speculative schedule while ensuring program correctness. Any divergence from the recorded instruction sequence causes execution to restart in program order from a previously checkpointed state. On a system capable of switching between big and little cores rapidly with low overheads, DynaMOS schedules 38% of execution on the little on average, increasing utilization of the energy-efficient core by 2.9X over prior work. This amounts to energy savings of 32% over execution on only big core, with an allowable 5% performance loss
Embedded System Design
A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues
Embedded System Design
A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues
Scheduling and locking in multiprocessor real-time operating systems
With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due to priority inversion can be bounded a priori. Several spinlock- and semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspension-oblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five asymptotically optimal locking protocols are designed and analyzed: a family of mutex, RW, and k-exclusion protocols for global, partitioned, and clustered scheduling that are asymptotically optimal in the suspension-oblivious case, and a mutex protocol for partitioned scheduling that is asymptotically optimal in the suspension-aware case. A LITMUSRT-based empirical evaluation is presented that shows these protocols to be practical
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