Improving the Performance and Endurance of Persistent Memory with Loose-Ordering Consistency

Persistent memory provides high-performance data persistence at main memory. Memory writes need to be performed in strict order to satisfy storage consistency requirements and enable correct recovery from system crashes. Unfortunately, adhering to such a strict order significantly degrades system performance and persistent memory endurance. This paper introduces a new mechanism, Loose-Ordering Consistency (LOC), that satisfies the ordering requirements at significantly lower performance and endurance loss. LOC consists of two key techniques. First, Eager Commit eliminates the need to perform a persistent commit record write within a transaction. We do so by ensuring that we can determine the status of all committed transactions during recovery by storing necessary metadata information statically with blocks of data written to memory. Second, Speculative Persistence relaxes the write ordering between transactions by allowing writes to be speculatively written to persistent memory. A speculative write is made visible to software only after its associated transaction commits. To enable this, our mechanism supports the tracking of committed transaction ID and multi-versioning in the CPU cache. Our evaluations show that LOC reduces the average performance overhead of memory persistence from 66.9% to 34.9% and the memory write traffic overhead from 17.1% to 3.4% on a variety of workloads.Comment: This paper has been accepted by IEEE Transactions on Parallel and Distributed System

Improved Sequence-Based Speculation Techniques for Implementing Memory Consistency

This work presents BMW, a new design for speculative implementations of memory consistency models in shared-memory multiprocessors. BMW obtains the same performance as prior proposals, but achieves this performance while avoiding several undesirable attributes of prior proposals: non-scalable structures, per-word valid bits in the data cache, modifications to the cache coherence protocol, and global arbitration. BMW uses a read and write bit per cache block and a standard invalidation-based cache coherence protocol to perform conflict detection while speculating. While speculating, stores to block not in the cache are placed into a coalescing store buffer until those misses return. Stores are written speculatively to the primary cache, and non-speculative state is maintained by cleaning dirty blocks before being written speculatively. Speculative blocks are invalidated on abort and marked as non-speculative on commit. This organization allows for fast, local commits while avoiding a non-scalable store queue

A Safety-First Approach to Memory Models.

Sequential consistency (SC) is arguably the most intuitive behavior for a shared-memory multithreaded program. It is widely accepted that language-level SC could significantly improve programmability of a multiprocessor system. However, efficiently supporting end-to-end SC remains a challenge as it requires that both compiler and hardware optimizations preserve SC semantics. Current concurrent languages support a relaxed memory model that requires programmers to explicitly annotate all memory accesses that can participate in a data-race ("unsafe" accesses). This requirement allows compiler and hardware to aggressively optimize unannotated accesses, which are assumed to be data-race-free ("safe" accesses), while still preserving SC semantics. However, unannotated data races are easy for programmers to accidentally introduce and are difficult to detect, and in such cases the safety and correctness of programs are significantly compromised. This dissertation argues instead for a safety-first approach, whereby every memory operation is treated as potentially unsafe by the compiler and hardware unless it is proven otherwise. The first solution, DRFx memory model, allows many common compiler and hardware optimizations (potentially SC-violating) on unsafe accesses and uses a runtime support to detect potential SC violations arising from reordering of unsafe accesses. On detecting a potential SC violation, execution is halted before the safety property is compromised. The second solution takes a different approach and preserves SC in both compiler and hardware. Both SC-preserving compiler and hardware are also built on the safety-first approach. All memory accesses are treated as potentially unsafe by the compiler and hardware. SC-preserving hardware relies on different static and dynamic techniques to identify safe accesses. Our results indicate that supporting SC at the language level is not expensive in terms of performance and hardware complexity. The dissertation also explores an extension of this safety-first approach for data-parallel accelerators such as Graphics Processing Units (GPUs). Significant microarchitectural differences between CPU and GPU require rethinking of efficient solutions for preserving SC in GPUs. The proposed solution based on our SC-preserving approach performs nearly on par with the baseline GPU that implements a data-race-free-0 memory model.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120794/1/ansingh_1.pd

Efficient fine-grained virtual memory

Virtual memory in modern computer systems provides a single abstraction of the memory hierarchy. By hiding fragmentation and overlays of physical memory, virtual memory frees applications from managing physical memory and improves programmability. However, virtual memory often introduces noticeable overhead. State-of-the-art systems use a paged virtual memory that maps virtual addresses to physical addresses in page granularity (typically 4 KiB ).This mapping is stored as a page table. Before accessing physically addressed memory, the page table is accessed to translate virtual addresses to physical addresses. Research shows that the overhead of accessing the page table can even exceed the execution time for some important applications. In addition, this fine-grained mapping changes the access patterns between virtual and physical address spaces, introducing difficulties to many architecture techniques, such as caches and prefecthers. In this dissertation, I propose architecture mechanisms to reduce the overhead of accessing and managing fine-grained virtual memory without compromising existing benefits. There are three main contributions in this dissertation. First, I investigate the impact of address translation on cache. I examine the restriction of virtually indexed, physically tagged (VIPT) caches with fine-grained paging and conclude that this restriction may lead to sub-optimal cache designs. I introduce a novel cache strategy, speculatively indexed, physically tagged (SIPT) to enable flexible cache indexing under fine-grained page mapping. SIPT speculates on the value of a few more index bits (1 - 3 in our experiments) to access the cache speculatively before translation, and then verify that the physical tag matches after translation. Utilizing the fact that a simple relation generally exists between virtual and physical addresses, because memory allocators often exhibit contiguity, I also propose low-cost mechanisms to predict and correct potential mis-speculations. Next, I focus on reducing the overhead of address translation for fine-grained virtual memory. I propose a novel architecture mechanism, Embedded Page Translation Information (EMPTI), to provide general fine-grained page translation information on top of coarse-grained virtual memory. EMPTI does so by speculating that a virtual address is mapped to a pre-determined physical location and then verifying the translation with a very-low-cost access to metadata embedded with data. Coarse-grained virtual memory mechanisms (e.g., segmentation) are used to suggest the pre-determined physical location for each virtual page. Overall, EMPTI achieves the benefits of low overhead translation while keeping the flexibility and programmability of fine-grained paging. Finally, I improve the efficiency of metadata caching based on the fact that memory mapping contiguity generally exists beyond a page boundary. In state-of-the-art architectures, caches treat PTEs (page table entries) as regular data. Although this is simple and straightforward, it fails to maximize the storage efficiency of metadata. Each page in the contiguously mapped region costs a full 8-byte PTE. However, the delta between virtual addresses and physical addresses remain the same and most metadata are identical. I propose a novel microarchitectural mechanism that expands the effective PTE storage in the last-level-cache (LLC) and reduces the number of page-walk accesses that miss the LLC.Electrical and Computer Engineerin

Survey on Combinatorial Register Allocation and Instruction Scheduling

Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization

レイテンシ耐性を持つベクトルプロセッサアーキテクチャに関する研究

Tohoku University博士（情報科学）thesi

URSIM reference manual

technical reportSimulation has emerged as an important method for evaluating new ideas in both uniprocessor and multiprocessor architecture. Compared to building real hardware, simulation provides at least two advantages. First, it provides the flexibility to modify various architectural parameters and components and to analyze the benefits of such modifications. Second, simulation allows detailed statistics collection, providing a better understanding of the tradcoffs involved and facilitating further performance tuning

Fast Linear Programming through Transprecision Computing on Small and Sparse Data

A plethora of program analysis and optimization techniques rely on linear programming at their heart. However, such techniques are often considered too slow for production use. While today’s best solvers are optimized for complex problems with thousands of dimensions, linear programming, as used in compilers, is typically applied to small and seemingly trivial problems, but to many instances in a single compilation run. As a result, compilers do not benefit from decades of research on optimizing large-scale linear programming. We design a simplex solver targeted at compilers. A novel theory of transprecision computation applied from individual elements to full data-structures provides the computational foundation. By carefully combining it with optimized representations for small and sparse matrices and specialized small-coefficient algorithms, we (1) reduce memory traffic, (2) exploit wide vectors, and (3) use low-precision arithmetic units effectively. We evaluate our work by embedding our solver into a state-of-the-art integer set library and implement one essential operation, coalescing, on top of our transprecision solver. Our evaluation shows more than an order-of-magnitude speedup on the core simplex pivot operation and a mean speedup of 3.2x (vs. GMP) and 4.6x (vs. IMath) for the optimized coalescing operation. Our results demonstrate that our optimizations exploit the wide SIMD instructions of modern microarchitectures effectively. We expect our work to provide foundations for a future integer set library that uses transprecision arithmetic to accelerate compiler analyses.ISSN:2475-142