Improving processor efficiency by exploiting common-case behaviors of memory instructions

Processor efficiency can be described with the help of a number of  desirable effects or metrics, for example, performance, power, area, design complexity and access latency. These metrics serve as valuable tools used in designing new processors and they also act as  effective standards for comparing current processors. Various factors impact the efficiency of modern out-of-order processors and one important factor is the manner in which instructions are processed through the processor pipeline. In this dissertation research, we study the impact of load and store instructions (collectively known as memory instructions) on processor efficiency,  and show how to improve efficiency by exploiting common-case or  predictable patterns in the behavior of memory instructions. The memory behavior patterns that we focus on in our research are the predictability of memory dependences, the predictability in data forwarding patterns,   predictability in instruction criticality and conservativeness in resource allocation and deallocation policies. We first design a scalable  and high-performance memory dependence predictor and then apply accurate memory dependence prediction to improve the efficiency of the fetch engine of a simultaneous multi-threaded processor. We then use predictable data forwarding patterns to eliminate power-hungry  hardware in the processor with no loss in performance.  We then move to  studying instruction criticality to improve  processor efficiency. We study the behavior of critical load instructions  and propose applications that can be optimized using  predictable, load-criticality  information. Finally, we explore conventional techniques for allocation and deallocation  of critical structures that process memory instructions and propose new techniques to optimize the same.  Our new designs have the potential to reduce  the power and the area required by processors significantly without losing  performance, which lead to efficient designs of processors.Ph.D.Committee Chair: Loh, Gabriel H.; Committee Member: Clark, Nathan; Committee Member: Jaleel, Aamer; Committee Member: Kim, Hyesoon; Committee Member: Lee, Hsien-Hsin S.; Committee Member: Prvulovic, Milo

Fire-and-Forget: Load/Store Scheduling with No Store Queue at all

Modern processors use CAM-based load and store queues (LQ/SQ) to support out-of-order memory scheduling and store-to-load forwarding. However, the LQ and SQ scale poorly for the sizes required for large-window, high-ILP processors. Past research has proposed ways to make the SQ more scalable by reorganizing the CAMs or using non-associative structures. In particular, the Store Queue Index Prediction (SQIP) approach allows for load instructions to predict the exact SQ index of a sourcing store and access the SQ in a much simpler and more scalable RAMbased fashion. The reason why SQIP works is that loads that receive data directly from stores will usually receive the data from the same store each time. In our work, we take a slightly different view on the underlying observation used by SQIP: a store that forwards data to a load usually forwards to the same load each time. This subtle change in perspective leads to our “Fire-and-Forget ” (FnF) scheme for load/store scheduling and forwarding that results in the complete elimination of the store queue. The idea is that stores issue out of the reservation stations like regular instructions, and any store that forwards data to a load will use a predicted LQ index to directly write the value to the LQ entry without any associative logic. Any mispredictions/misforwardings are detected by a low-overhead pre-commit re-execution mechanism. Our original goal for FnF was to design a more scalable memory scheduling microarchitecture than the previously proposed approaches without degrading performance. The relative infrequency of store-to-load forwarding, accurate LQ index prediction, and speculative cloaking actually combine to enable FnF to slightly out-perform the competition. Specifically, our simulation results show that our SQless Fire-and-Forget provides a 3.3 % speedup over a processor using a conventional fully-associative SQ. 1

PEEP: Exploiting Predictability of Memory Dependences in SMT Processors

Simultaneous Multithreading (SMT) attempts to keep a dynamically scheduled processor’s resources busy with work from multiple independent threads. Threads with longlatency stalls, however, can lead to a reduction in overall throughput because they occupy many of the critical processor resources. In this work, we first study the interaction between stalls caused by ambiguous memory dependences and SMT processing. We then propose the technique of Proactive Exclusion (PE) where the SMT fetch unit stops fetching from a thread when a memory dependence is predicted to exist. However, after the dependence has been resolved, the thread is delayed waiting for new instructions to be fetched and delivered down the front-end pipeline. So we introduce an Early Parole (EP) mechanism that exploits the predictability of dependence-resolution delays to restart fetch of an excluded thread so that the instructions reach the execution core just as the original dependence resolves. We show that combining these two techniques (PEEP) yields a 16.9 % throughput improvement on a 4-way SMT processor that supports speculative memory disambiguation. These strong results indicate that a fetch policy that is cognizant of future stalls considerably improves the throughput of an SMT machine. 1

Zesto: A Cycle-Level Simulator for Highly Detailed Microarchitecture Exploration

For academic computer architecture research, a large number of publicly available simulators make use of relatively simple abstractions for the microarchitecture of the processor pipeline. For some types of studies, such as those for multi-core cache coherence designs, a simple pipeline model may suffice. For detailed microarchitecture research, such as those that are sensitive to the exact behavior of outof-order scheduling, ALU and bypass network contention, and resource management (e.g., RS and ROB entries), an over-simplified model is not representative of modern processor organizations. We present a new timing simulator that models a modern x86 microarchitecture at a very low level, including out-of-order scheduling and execution that much more closely mirrors current implementations, a detailed cache/memory hierarchy, as well as many x86specific microarchitecture features (e.g., simple vs. complex decoders, micro-op decomposition and fusion, microcode lookup overhead for long/complex x86 instructions). 1

Criticality-based optimizations for efficient load processing

Some instructions have more impact on processor performance than others. Identification of these critical instructions can be used to modify and improve instruction processing. Previous work has shown that the criticality of instructions can be dynamically predicted with high accuracy, and that this information can be leveraged to optimize the performance of load value prediction and instruction steering for clustered architectures. In this work, we revisit the idea of criticality, but we propose several processor enhancements that can exploit criticality information and can be directly applied to modern x86 microarchitectures. For the investment of a small (less than 1KB) criticality predictor, we can make a conventional single-read-port data cache achieve the performance of an ideal dual-read-port cache, yielding an average 10 % performance improvement. Our remaining techniques can reuse the predictor (i.e., no additional overhead) to further optimize other aspects of load processing (e.g., caching decisions, store-to-load forwarding, etc.), yielding an overall performance improvement of 16 % over a conventional processor. Some of these techniques also allow us to decrease power and area costs for several related hardware structures. 1