The case for a scalable coherence protocol for complex on-chip cache hierarchies in many-core systems

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Exploiting commutativity to reduce the cost of updates to shared data in cache-coherent systems

We present Coup, a technique to lower the cost of updates to shared data in cache-coherent systems. Coup exploits the insight that many update operations, such as additions and bitwise logical operations, are commutative: they produce the same final result regardless of the order they are performed in. Coup allows multiple private caches to simultaneously hold update-only permission to the same cache line. Caches with update-only permission can locally buffer and coalesce updates to the line, but cannot satisfy read requests. Upon a read request, Coup reduces the partial updates buffered in private caches to produce the final value. Coup integrates seamlessly into existing coherence protocols, requires inexpensive hardware, and does not affect the memory consistency model. We apply Coup to speed up single-word updates to shared data. On a simulated 128-core, 8-socket system, Coup accelerates state-of-the-art implementations of update-heavy algorithms by up to 2.4×.Center for Future Architectures ResearchNational Science Foundation (U.S.) (CAREER-1452994)Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Grier Presidential Fellowship)Microelectronics Advanced Research CorporationUnited States. Defense Advanced Research Projects Agenc

Doctor of Philosophy

dissertationIn recent years, a number of trends have started to emerge, both in microprocessor and application characteristics. As per Moore's law, the number of cores on chip will keep doubling every 18-24 months. International Technology Roadmap for Semiconductors (ITRS) reports that wires will continue to scale poorly, exacerbating the cost of on-chip communication. Cores will have to navigate an on-chip network to access data that may be scattered across many cache banks. The number of pins on the package, and hence available off-chip bandwidth, will at best increase at sublinear rate and at worst, stagnate. A number of disruptive memory technologies, e.g., phase change memory (PCM) have begun to emerge and will be integrated into the memory hierarchy sooner than later, leading to non-uniform memory access (NUMA) hierarchies. This will make the cost of accessing main memory even higher. In previous years, most of the focus has been on deciding the memory hierarchy level where data must be placed (L1 or L2 caches, main memory, disk, etc.). However, in modern and future generations, each level is getting bigger and its design is being subjected to a number of constraints (wire delays, power budget, etc.). It is becoming very important to make an intelligent decision about where data must be placed within a level. For example, in a large non-uniform access cache (NUCA), we must figure out the optimal bank. Similarly, in a multi-dual inline memory module (DIMM) non uniform memory access (NUMA) main memory, we must figure out the DIMM that is the optimal home for every data page. Studies have indicated that heterogeneous main memory hierarchies that incorporate multiple memory technologies are on the horizon. We must develop solutions for data management that take heterogeneity into account. For these memory organizations, we must again identify the appropriate home for data. In this dissertation, we attempt to verify the following thesis statement: "Can low-complexity hardware and OS mechanisms manage data placement within each memory hierarchy level to optimize metrics such as performance and/or throughput?" In this dissertation we argue for a hardware-software codesign approach to tackle the above mentioned problems at different levels of the memory hierarchy. The proposed methods utilize techniques like page coloring and shadow addresses and are able to handle a large number of problems ranging from managing wire-delays in large, shared NUCA caches to distributing shared capacity among different cores. We then examine data-placement issues in NUMA main memory for a many-core processor with a moderate number of on-chip memory controllers. Using codesign approaches, we achieve efficient data placement by modifying the operating system's (OS) page allocation algorithm for a wide variety of main memory architectures

TLB-Based Temporality-Aware Classification in CMPs with Multilevel TLBs

"© 2017 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."[EN] Recent proposals are based on classifying memory accesses into private or shared in order to process private accesses more efficiently and reduce coherence overhead. The classification mechanisms previously proposed are either not able to adapt to the dynamic sharing behavior of the applications or require frequent broadcast messages. Additionally, most of these classification approaches assume single-level translation lookaside buffers (TLBs). However, deeper and more efficient TLB hierarchies, such as the ones implemented in current commodity processors, have not been appropriately explored. This paper analyzes accurate classification mechanisms in multilevel TLB hierarchies. In particular, we propose an efficient data classification strategy for systems with distributed shared last-level TLBs. Our approach classifies data accounting for temporal private accesses and constrains TLB-related traffic by issuing unicast messages on first-level TLB misses. When our classification is employed to deactivate coherence for private data in directory-based protocols, it improves the directory efficiency and, consequently, reduces coherence traffic to merely 53.0%, on average. Additionally, it avoids some of the overheads of previous classification approaches for purely private TLBs, improving average execution time by nearly 9% for large-scale systems.This work has been jointly supported by the MINECO and European Commission (FEDER funds) under the project TIN2015-66972-C5-1-R and TIN2015-66972-C5-3-R and the Fundacion Seneca-Agencia de Ciencia y Tecnologia de la Region de Murcia under the project Jovenes Lideres en Investigacion 18956/JLI/13.Esteve Garcia, A.; Ros Bardisa, A.; Gómez Requena, ME.; Robles Martínez, A.; Duato Marín, JF. (2017). TLB-Based Temporality-Aware Classification in CMPs with Multilevel TLBs. IEEE Transactions on Parallel and Distributed Systems. 28(8):2401-2413. https://doi.org/10.1109/TPDS.2017.2658576S2401241328

Avalanche: A communication and memory architecture for scalable parallel computing

technical reportAs the gap between processor and memory speeds widens?? system designers will inevitably incorpo rate increasingly deep memory hierarchies to maintain the balance between processor and memory system performance At the same time?? most communication subsystems are permitted access only to main memory and not a processor s top level cache As memory latencies increase?? this lack of integration between the memory and communication systems will seriously impede interprocessor communication performance and limit e ective scalability In the Avalanche project we are re designing the memory architecture of a commercial RISC multiprocessor?? the HP PA RISC ?? to include a new multi level context sensitive cache that is tightly coupled to the communication fabric The primary goal of Avalanche s integrated cache and communication controller is attack ing end to end communication latency in all of its forms This includes cache misses induced by excessive invalidations and reloading of shared data by write invalidate coherence protocols and cache misses induced by depositing incoming message data in main memory and faulting it into the cache An execution driven simulation study of Avalanche s architecture indicates that it can reduce cache stalls by and overall execution times b

Avalanche: A communication and memory architecture for scalable parallel computing

technical reportAs the gap between processor and memory speeds widens, system designers will inevitably incorporate increasingly deep memory hierarchies to maintain the balance between processor and memory system performance. At the same time, most communication subsystems are permitted access only to main memory and not a processor's top level cache. As memory latencies increase, this lack of integration between the memory and communication systems will seriously impede interprocessor communication performance and limit effective scalability. In the Avalanche project we are redesigning the memory architecture of a commercial RISC multiprocessor, the HP PA-RISC 7100, to include a new multi-level context sensitive cache that is tightly coupled to the communication fabric. The primary goal of Avalanche's integrated cache and communication controller is attacking end to end communication latency in all of its forms. This includes cache misses induced by excessive invalidations and reloading of shared data by write-invalidate coherence protocols and cache misses induced by depositing incoming message data in main memory and faulting it into the cache. An execution-driven simulation study of Avalanche's architecture indicates that it can reduce cache stalls by 5-60% and overall execution times by 10-28%

Locality-oblivious cache organization leveraging single-cycle multi-hop NoCs

Locality has always been a critical factor in on-chip data placement on CMPs as accessing further-away caches has in the past been more costly than accessing nearby ones. Substantial research on locality-aware designs have thus focused on keeping a copy of the data private. However, this complicatesthe problem of data tracking and search/invalidation; tracking the state of a line at all on-chip caches at a directory or performing full-chip broadcasts are both non-scalable and extremely expensive solutions. In this paper, we make the case for Locality-Oblivious Cache Organization (LOCO), a CMP cache organization that leverages the on-chip network to create virtual single-cycle paths between distant caches, thus redefining the notion of locality. LOCO is a clustered cache organization, supporting both homogeneous and heterogeneous cluster sizes, and provides near single-cycle accesses to data anywhere within the cluster, just like a private cache. Globally, LOCO dynamically creates a virtual mesh connecting all the clusters, and performs an efficient global data search and migration over this virtual mesh, without having to resort to full-chip broadcasts or perform expensive directory lookups. Trace-driven and full system simulations running SPLASH-2 and PARSEC benchmarks show that LOCO improves application run time by up to 44.5% over baseline private and shared cache.Semiconductor Research CorporationUnited States. Defense Advanced Research Projects Agency (Semiconductor Technology Advanced Research Network

Scaling Distributed Cache Hierarchies through Computation and Data Co-Scheduling

Cache hierarchies are increasingly non-uniform, so for systems to scale efficiently, data must be close to the threads that use it. Moreover, cache capacity is limited and contended among threads, introducing complex capacity/latency tradeoffs. Prior NUCA schemes have focused on managing data to reduce access latency, but have ignored thread placement; and applying prior NUMA thread placement schemes to NUCA is inefficient, as capacity, not bandwidth, is the main constraint. We present CDCS, a technique to jointly place threads and data in multicores with distributed shared caches. We develop novel monitoring hardware that enables fine-grained space allocation on large caches, and data movement support to allow frequent full-chip reconfigurations. On a 64-core system, CDCS outperforms an S-NUCA LLC by 46% on average (up to 76%) in weighted speedup and saves 36% of system energy. CDCS also outperforms state-of-the-art NUCA schemes under different thread scheduling policies.National Science Foundation (U.S.) (Grant CCF-1318384)Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Jacobs Presidential Fellowship)United States. Defense Advanced Research Projects Agency (PERFECT Contract HR0011-13-2-0005

Design and Implementation of a Chip Multiprocessor with an Efficient Multilevel Cache System

Computer designers utilize the recent huge advances in Very Large Scale Integration (VLSI) to get Chip Multiprocessor (CMP) by placing several processors on the same chip die. The CMP is the dominant architecture to improve the performance of the current computing systems. However, accessing a shared data by several processors is a primary challenge in CMP. The data consistency must be reached among all memory hierarchies to ensure correct behavior and higher performance. This paper, proposed a CMP with an efficient multilevel cache system, which enhances miss rate and latency (penalty) by designing and implementation of different write policies with two levels of cache. The proposed system is implemented and tested using Hardware Description Language (VHDL) on Altera’s FPGA chip. The results show that a combination of write-through without buffer for the first level and write-back for the second level offers a clear improvement on the multilevel cache system performance