Jack Sampson

Conservation cores: reducing the energy of mature computations

Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. In this regime, specialized, energy-efficient processors can increase parallelism by reducing the per-computation power requirements and allowing more computations to execute under the same power budget. To pursue this goal, this paper introduces conservation cores. Conservation cores, or c-cores, are specialized processors that focus on reducing energy and energy-delay instead of increasing performance. This focus on energy makes c-cores an excellent match for many applications that would be poor candidates for hardware acceleration (e.g., irregular integer codes). We present a toolchain for automatically synthesizing c-cores from application source code and demonstrate that they can significantly reduce energy and energy-delay for a wide range of applications. The c-cores support patching, a form of targeted reconfigurability, that allows them to adapt to new versions of the software they target. Our results show that conservation cores can reduce energy consumption by up to 16.0x for functions and by up to 2.1x for whole applications, while patching can extend the useful lifetime of individual c-cores to match that of conventional processors.

The GreenDroid Mobile Application Processor: An Architecture for Silicon's Dark Future

This article discusses about Greendroid mobile Application Processor. Dark silicon has emerged as the fundamental limiter in modern processor design. The Greendroid mobile application processor demonstrates an approach that uses dark silicon to execute general-purpose smart phone applications with less energy than todays most energy efficient designs.

Managing distributed ups energy for effective power capping in data centers

Power over-subscription can reduce costs for modern data centers. However, designing the power infrastructure for a lower operating power point than the aggregated peak power of all servers requires dynamic techniques to avoid high peak power costs and, even worse, tripping circuit breakers. This work presents an architecture for distributed per-server UPSs that stores energy during low activity periods and uses this energy during power spikes. This work leverages the distributed nature of the UPS batteries and develops policies that prolong the duration of their usage. The specific approach shaves 19.4% of the peak power for modern servers, at no cost in performance, allowing the installation of 24% more servers within the same power budget. More servers amortize infrastructure costs better and, hence, reduce total cost of ownership per server by 6.3%.

The Strong correlation Between Code Signatures and Performance

A recent study examined the use of sampled hardware counters to create sampled code signatures. This approach is attractive because sampled code signatures can be quickly gathered for any application. The conclusion of their study was that there exists a fuzzy correlation between sampled code signatures and performance predictability. The paper raises the question of how much information is lost in the sampling process, and our paper focuses on examining this issue. We first focus on showing that there exists a strong correlation between code signatures and performance. We then examine the relationship between sampled and full code signatures, and how these affect performance predictability. Our results confirm that there is a fuzzy correlation found in recent work for the SPEC programs with sampled code signatures, but that a strong correlation exists with full code signatures. In addition, we propose converting the sampled instruction counts, used in the prior work, into sampled code signatures representing loop and procedure execution frequencies. These sampled loop and procedure code signatures allow phase analysis to more accurately and easily find patterns, and they correlate better with performance

QsCores: trading dark silicon for scalable energy efficiency with quasi-specific cores

Transistor density continues to increase exponentially, but power dissipation per transistor is improving only slightly with each generation of Moores law. Given the constant chip-level power budgets, this exponentially decreases the percentage of transistors that can switch at full frequency with each technology generation. Hence, while the transistor budget continues to increase exponentially, the power budget has become the dominant limiting factor in processor design. In this regime, utilizing transistors to design specialized cores that optimize energy-per-computation becomes an effective approach to improve system performance.

Architecture exploration for ambient energy harvesting nonvolatile processors

Energy harvesting has been widely investigated as a promising method of providing power for ultra-low-power applications. Such energy sources include solar energy, radio-frequency (RF) radiation, piezoelectricity, thermal gradients, etc. However, the power supplied by these sources is highly unreliable and dependent upon ambient environment factors. Hence, it is necessary to develop specialized systems that are tolerant to this power variation, and also capable of making forward progress on the computation tasks. The simulation platform in this paper is calibrated using measured results from a fabricated nonvolatile processor and used to explore the design space for a nonvolatile processor with different architectures, different input power sources, and policies for maximizing forward progress.

Detecting phases in parallel applications on shared memory architectures

Most programs are repetitive, where similar behavior can be seen at different execution times. Algorithms have been proposed that automatically group similar portions of a programs execution into phases, where samples of execution in the same phase have homogeneous behavior and similar resource requirements. In this paper, we examine applying these phase analysis algorithms and how to adapt them to parallel applications running on shared memory processors. Our approach relies on a separate representation of each threads activity. We first focus on showing its ability to identify similar intervals of execution across threads for a single run. We then show that it is effective at identifying similar behavior of a program when the number of threads is varied between runs. This can be used by developers to examine how different phases scale across different number of threads. Finally, we examine using the phase analysis to pick simulation points to guide multithreaded simulation.

Exploiting Fine-Grained Data Parallelism with Chip Multiprocessors and Fast Barriers

We examine the ability of CMPs, due to their lower on-chip communication latencies, to exploit data parallelism at inner-loop granularities similar to that commonly targeted by vector machines. Parallelizing code in this manner leads to a high frequency of barriers, and we explore the impact of different barrier mechanisms upon the efficiency of this approach. To further exploit the potential of CMPs for fine-grained data parallel tasks, we present barrier filters, a mechanism for fast barrier synchronization on-chip multi-processors to enable vector computations to be efficiently distributed across the cores of a CMP. We ensure that all threads arriving at a barrier require an unavailable cache line to proceed, and, by placing additional hardware in the shared portions of the memory subsystem, we starve their requests until they all have arrived. Specifically, our approach uses invalidation requests to both make cache lines unavailable and identify when a thread has reached the barrier. We examine two types of barrier filters, one synchronizing through instruction cache lines, and the other through data cache lines

Exploiting program microarchitecture independent characteristics and phase behavior for reduced benchmark suite simulation

Modern architecture research relies heavily on detailed pipeline simulation. Simulating the full execution of an industry standard benchmark can take weeks to complete. Simulating the full execution of the whole benchmark suite for one architecture configuration can take months. To address this issue researchers have examined using targetted sampling based on phase behavior to significantly reduce the simulation time of each program in the benchmark suite. However, even with this sampling approach, simulating the full benchmark suite across a large range of architecture designs can take days to weeks to complete. The goal of this paper is to further reduce simulation time for architecture design space exploration. We reduce simulation time by finding similarity between benchmarks and program inputs at the level of samples (100M instructions of execution). This allows us to use a representative sample of execution from one benchmark to accurately represent a sample of execution of other benchmarks and inputs. The end result of our analysis is a small number of sample points of execution. These are selected across the whole benchmark suite in order to accurately represent the complete simulation of the whole benchmark suite for design space exploration. We show that this provides approximately the same accuracy as the SimPoint sampling approach while reducing the number of simulated instructions by a factor of 1.5.

Ambient energy harvesting nonvolatile processors: from circuit to system

Energy harvesting is gaining more and more attentions due to its characteristics of ultra-long operation time without maintenance. However, frequent unpredictable power failures from energy harvesters bring performance and reliability challenges to traditional processors. Nonvolatile processors are promising to solve such a problem due to their advantage of zero leakage and efficient backup and restore operations. To optimize the nonvolatile processor design, this paper proposes new metrics of nonvolatile processors to consider energy harvesting factors for the first time. Furthermore, we explore the nonvolatile processor design from circuit to system level. A prototype of energy harvesting nonvolatile processor is set up and experimental results show that the proposed performance metric meets the measured results by less than 6.27% average errors. Finally, the energy consumption of nonvolatile processor is analyzed under different benchmarks.