Performance asymmetry in multicore architectures arises when individual cores have different performance. Building such multicore processors is desirable because many simple cores together provide high parallel performance while a few complex cores ensure high serial performance. However, application developers typically assume computational cores provide equal performance, and performance asymmetry breaks this assumption.This paper is concerned with the behavior of commercial applications running on performance asymmetric systems. We present the first study investigating the impact of performance asymmetry on a wide range of commercial applications using a hardware prototype. We quantify the impact of asymmetry on an application's performance variance when run multiple times, and the impact on the application's scalability.Performance asymmetry adversely affects behavior of many workloads. We study ways to eliminate these effects. In addition to asymmetry-aware operating system kernels, the application often itself needs to be aware of performance asymmetry for stable and scalable performance.
Increased integration in the form of multiple processor cores on a single die, relatively constant die sizes, shrinking power envelopes, and emerging applications create a new challenge for processor architects. How to build a processor that provides high single-thread performance and enables multiple of these to be placed on the same die for high throughput while dynamically adapting for future applications? Conventional approaches for high single-thread performance rely on large and complex cores to sustain a large instruction window for memory tolerance, making them unsuitable for multi-core chips. We present Continual Flow Pipelines (CFP) as a new non-blocking processor pipeline architecture that achieves the performance of a large instruction window without requiring cycle-critical structures such as the scheduler and register file to be large. We show that to achieve benefits of a large instruction window, inefficiencies in management of both the scheduler and register file must be addressed, and we propose a unified solution. The non-blocking property of CFP keeps key processor structures affecting cycle time and power (scheduler, register file), and die size (second level cache) small. The memory latency-tolerant CFP core allows multiple cores on a single die while outperforming current processor cores for single-thread applications.
Increased integration in the form of multiple processor cores on a single die, relatively constant die sizes, shrinking power envelopes, and emerging applications create a new challenge for processor architects. How to build a processor that provides high single-thread performance and enables multiple of these to be placed on the same die for high throughput while dynamically adapting for future applications? Conventional approaches for high single-thread performance rely on large and complex cores to sustain a large instruction window for memory tolerance, making them unsuitable for multi-core chips. We present Continual Flow Pipelines (CFP) as a new non-blocking processor pipeline architecture that achieves the performance of a large instruction window without requiring cycle-critical structures such as the scheduler and register file to be large. We show that to achieve benefits of a large instruction window, inefficiencies in management of both the scheduler and register file must be addressed, and we propose a unified solution. The non-blocking property of CFP keeps key processor structures affecting cycle time and power (scheduler, register file), and die size (second level cache) small. The memory latency-tolerant CFP core allows multiple cores on a single die while outperforming current processor cores for single-thread applications.
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