Dynamic Selective Devectorization for Efficient Power Gating of SIMD Units in a HW/SW Co-Designed Environment

Leakage power is a growing concern in current and future microprocessors. Functional units of microprocessors are responsible for a major fraction of this power. Therefore, reducing functional unit leakage has received much attention in the recent years. Power gating is one of the most widely used techniques to minimize leakage energy. Power gating turns off the functional units during the idle periods to reduce the leakage. Therefore, the amount of leakage energy savings is directly proportional to the idle time duration. This paper focuses on increasing the idle interval for the higher SIMD lanes. The applications are profiled dynamically, in a HW/SW co-designed environment, to find the higher SIMD lanes usage pattern. If the higher lanes need to be turned-on for small time periods, the corresponding portion of the code is devectorized to keep the higher lanes off. The devectorized code is executed on the lowest SIMD lane. Our experimental results show average SIMD accelerator energy savings of 12% and 24% relative to power gating, for SPECFP2006 and Physicsbench. Moreover, the slowdown caused due to devectorization is less than 1%.Postprint (author’s final draft

Optimizing SIMD execution in HW/SW co-designed processors

SIMD accelerators are ubiquitous in microprocessors from different computing domains. Their high compute power and hardware simplicity improve overall performance in an energy efficient manner. Moreover, their replicated functional units and simple control mechanism make them amenable to scaling to higher vector lengths. However, code generation for these accelerators has been a challenge from the days of their inception. Compilers generate vector code conservatively to ensure correctness. As a result they lose significant vectorization opportunities and fail to extract maximum benefits out of SIMD accelerators. This thesis proposes to vectorize the program binary at runtime in a speculative manner, in addition to the compile time static vectorization. There are different environments that support runtime profiling and optimization support required for dynamic vectorization, one of most prominent ones being: 1) Dynamic Binary Translators and Optimizers (DBTO) and 2) Hardware/Software (HW/SW) Co-designed Processors. HW/SW co-designed environment provides several advantages over DBTOs like transparent incorporations of new hardware features, binary compatibility, etc. Therefore, we use HW/SW co-designed environment to assess the potential of speculative dynamic vectorization. Furthermore, we analyze vector code generation for wider vector units and find out that even though SIMD accelerators are amenable to scaling from the hardware point of view, vector code generation at higher vector length is even more challenging. The two major factors impeding vectorization for wider SIMD units are: 1) Reduced dynamic instruction stream coverage for vectorization and 2) Large number of permutation instructions. To solve the first problem we propose Variable Length Vectorization that iteratively vectorizes for multiple vector lengths to improve dynamic instruction stream coverage. Secondly, to reduce the number of permutation instructions we propose Selective Writing that selectively writes to different parts of a vector register and avoids permutations. Finally, we tackle the problem of leakage energy in SIMD accelerators. Since SIMD accelerators consume significant amount of real estate on the chip, they become the principle source of leakage if not utilized judiciously. Power gating is one of the most widely used techniques to reduce leakage energy of functional units. However, power gating has its own energy and performance overhead associated with it. We propose to selectively devectorize the vector code when higher SIMD lanes are used intermittently. This selective devectorization keeps the higher SIMD lanes idle and power gated for maximum duration. Therefore, resulting in overall leakage energy reduction.Postprint (published version

細粒度電源遮断制御および不揮発性素子を用いたＬＳIの低消費電力化技術の研究

芝浦工業大学2016年

Power Management for Deep Submicron Microprocessors

As VLSI technology scales, the enhanced performance of smaller transistors comes at the expense of increased power consumption. In addition to the dynamic power consumed by the circuits there is a tremendous increase in the leakage power consumption which is further exacerbated by the increasing operating temperatures. The total power consumption of modern processors is distributed between the processor core, memory and interconnects. In this research two novel power management techniques are presented targeting the functional units and the global interconnects. First, since most leakage control schemes for processor functional units are based on circuit level techniques, such schemes inherently lack information about the operational profile of higher-level components of the system. This is a barrier to the pivotal task of predicting standby time. Without this prediction, it is extremely difficult to assess the value of any leakage control scheme. Consequently, a methodology that can predict the standby time is highly beneficial in bridging the gap between the information available at the application level and the circuit implementations. In this work, a novel Dynamic Sleep Signal Generator (DSSG) is presented. It utilizes the usage traces extracted from cycle accurate simulations of benchmark programs to predict the long standby periods associated with the various functional units. The DSSG bases its decisions on the current and previous standby state of the functional units to accurately predict the length of the next standby period. The DSSG presents an alternative to Static Sleep Signal Generation (SSSG) based on static counters that trigger the generation of the sleep signal when the functional units idle for a prespecified number of cycles. The test results of the DSSG are obtained by the use of a modified RISC superscalar processor, implemented by SimpleScalar, the most widely accepted open source vehicle for architectural analysis. In addition, the results are further verified by a Simultaneous Multithreading simulator implemented by SMTSIM. Leakage saving results shows an increase of up to 146% in leakage savings using the DSSG versus the SSSG, with an accuracy of 60-80% for predicting long standby periods. Second, chip designers in their effort to achieve timing closure, have focused on achieving the lowest possible interconnect delay through buffer insertion and routing techniques. This approach, though, taxes the power budget of modern ICs, especially those intended for wireless applications. Also, in order to achieve more functionality, die sizes are constantly increasing. This trend is leading to an increase in the average global interconnect length which, in turn, requires more buffers to achieve timing closure. Unconstrained buffering is bound to adversely affect the overall chip performance, if the power consumption is added as a major performance metric. In fact, the number of global interconnect buffers is expected to reach hundreds of thousands to achieve an appropriate timing closure. To mitigate the impact of the power consumed by the interconnect buffers, a power-efficient multi-pin routing technique is proposed in this research. The problem is based on a graph representation of the routing possibilities, including buffer insertion and identifying the least power path between the interconnect source and set of sinks. The novel multi-pin routing technique is tested by applying it to the ISPD and IBM benchmarks to verify the accuracy, complexity, and solution quality. Results obtained indicate that an average power savings as high as 32% for the 130-nm technology is achieved with no impact on the maximum chip frequency

Improving the Energy Efficiency of Microprocessor Cores Through Accurate Resource Utilisation Prediction

CMOS technology scaling improves the speed and functionality of microprocessors by reducing the size of transistors. Static power dissipation also increases as a result of scaling however, and has been identified as a limiting factor in technology scaling. As current technology approaches that limit, techniques are required both at the technology-level and in the architecture design to reduce sub-threshold leakage, which accounts for the majority of static power dissipation. This thesis presents an approach to predict the idle periods of execution units at runtime and power-gate them during these periods to eliminate their static power leakage. We exploit similar execution characteristics across loop iterations to build a prediction of the units required to execute an entire loop from the units used over the first few iterations. The utilisation of each execution unit is monitored for each iteration, and thresholds are used to determine which units should be power-gated for the remainder of the loop. Three techniques are presented: Loop-Directed Mothballing (LDM), Extended Loop-Directed Mothballing (ELDM) and schedule balancing. LDM power-gates execution units only during innermost loops, which are simple to detect at runtime. ELDM extends this method to all loops using loop entry and exit information gathered offline. The balancing scheduler is developed to balance the types of instruction issued each cycle, to encourage reuse of execution units and make unnecessary units easier to detect. Extensive simulation using traces of 16 benchmarks from the SPEC CPU2006 suite demonstrates that LDM reduces the energy-delay product of our simulated superscalar processor by 10.3%. For traces with a low proportion of executed instructions inside innermost loops, ELDM improves the energy-delay product by up to 13% by allowing the technique to be applied to other loops in the trace. Employing schedule balancing with ELDM achieves similar savings, and simplifies the hardware required to make predictions