Despite high degrees of parallelism in terms of the number of chips and channels on state-of-the-art SSDs, resource contention continues to be a big impediment to boosting their performance for both read and write requests. This is particularly significant in the delays due to queueing for service from individual NAND-flash chips that can take dozens/hundreds of microseconds to perform the read/write operations. Owing to the no-write-in-place policy that is employed in flash chips, writes are inherently suited to be redirected to chips with lower load, in case their original destination chip is overloaded. However, to date, there has been no work to redirect read requests, since they cannot be serviced by other chips, which do not have the data. While blindly replicating all the data everywhere seems very promising from a read redirection perspective, doing so results in high space overheads, high write/replication overheads and lower endurance. This paper presents a novel approach to selective replication, wherein the popularity of data is used to figure out the "what", "how much", "where" and "when" questions for replication. Leveraging value locality/popularity, that is often observed in practice, popular data is replicated across multiple chips to provide more opportunities for dynamic read redirection to less loaded flash chips. Using extensive workload traces running over weeks from real systems, we show that our Read Redirected SSD (RR-SSD) can provide up to 45% improvement in read performance, with average improvement of 23.9%, and up to 40% improvement when considering both read and write requests, with 16% improvement on average.

In this paper, we present a novel cache design based on Multi-Level Cell Spin-Transfer Torque RAM (MLC STT-RAM) that can dynamically adjust the set capacity and associativity to efficiently use the full potential of MLC STT-RAM technology. We exploit the asymmetric nature of the MLC storage scheme to build cache lines featuring heterogeneous performances, that is, half of the cache lines are read-friendly, while the other half are write-friendly. Furthermore, we propose to opportunistically deactivate cache ways in underutilized sets to convert MLC to Single-Level Cell (SLC) mode, which features overall better performance and lifetime. Our ultimate goal is to build a cache architecture that combines the capacity advantages of MLC and performance/energy advantages of SLC. Our experimental evaluations show an average improvement of 43 percent in total numbers of conflict misses, 27 percent in memory access latency, 12 percent in system performance, and 26 percent in L3 access energy, with a slight degradation in lifetime (about 7 percent) compared to an SLC cache.

With Solid State Disks (SSDs) offering high degrees of parallelism, SSD controllers place data and direct requests to exploit the maximum offered hardware parallelism. In the quest to maximize parallelism and utilization, sub-requests of a request that are directed to different flash chips by the scheduler can experience differential wait times since their individual queues are not coordinated and load balanced at all times. Since the macro request is considered complete only when its last sub-request completes, some of its sub-requests that complete earlier have to necessarily wait for this last sub-request. This paper opens the door to a new class of schedulers to leverage such slack between sub-requests in order to improve response times. Specifically, the paper presents the design and implementation of a slack-enabled re-ordering scheduler, called Slacker, for sub-requests issued to each flash chip. Layered under a modern SSD request scheduler, Slacker estimates the slack of each incoming sub-request to a flash chip and allows them to jump ahead of existing sub-requests with sufficient slack so as to not detrimentally impact their response times. Slacker is simple to implement and imposes only marginal additions to the hardware. Using a spectrum of 21 workloads with diverse read-write characteristics, we show that Slacker provides as much as 19.5%, 13% and 14.5% improvement in response times, with average improvements of 12%, 6.5% and 8.5%, for write-intensive, read-intensive and read-write balanced workloads, respectively.

Limited write endurance is the main obstacle standing in the way of using phase change memory (PCM) in future computing systems. While several wear-leveling and hard-error tolerant techniques have been proposed for improving PCM lifetime, most of these approaches assume that the underlying memory uses a very simple write traffic reduction scheme (e.g., buffering, differential writes). In particular, most PCM prototypes/chips are equipped with an embedded circuit to support differential writes (DW) - on a write, only the bits that differ between the old and new data are updated. With DW, the bit-pattern of updates in a memory block is usually random, which limits the opportunity to exploit the resulting bit pattern for lifetime enhancement at an architecture level (e.g., using techniques such as wear-leveling and hard-error tolerance). This paper focuses on this inefficiency and proposes a solution based on data compression. Employing compression can improve the lifetime of the PCM memory. Using state-of-the-art compression schemes, the size of the compressed data is usually much smaller than the original data written back to memory from the last-level cache on an eviction. By storing data in a compressed format in the target memory block, first, we limit the number of bit flips to fewer memory cells, enabling more efficient intra-line wear-leveling and error recovery, and second, the unused bits in the memory block can be reused as replacements for faulty bits given the reduced size of the (compressed) data. It can also happen that for a portion of the memory blocks, the resulting compressed data is not very small. This can be due to increased data entropy introduced by compression, where the total number of bit flips will be increased over the baseline system. In this paper, we present an approach that provides collaborative operation of data compression, differential writes, wear-leveling and hard-error tolerant techniques targeting PCM memories. We propose approaches that reap the maximum benefits from compression, while also enjoying the benefits of techniques that reduce the number of high-entropy writes. Using an approach that combines different solutions, our mechanism tolerates 2.9× more cell failures per memory line and achieves a 4.3× increase in PCM memory lifetime, relative to our baseline state-of-the-art PCM DIMM memory.

Owing to negligible leakage current, high density and superior scalability, Spin-Transfer Torque RAM (STT-RAM) technology becomes one of the promising candidates for low power and high capacity on-chip caches in multicore systems. While STT-RAM read access latency is comparable to that of SRAM, write operations in STT-RAM are more challenging: writes are slow, consume a large energy, and the lifetime of STT-RAM is limited by the number of write operations to each cell. To overcome these challenges in STT-RAM caches, this paper explores the potential of eliminating redundant writes using the phenomenon of frequent value locality (FVL). According to FLV, few distinct values appear in a large fraction of memory transactions, with emphasis on cache memories in this work. By leveraging frequent value locality, we propose a novel value-based hybrid (STT-RAM +, SRAM) cache that has benefits of both SRAM and STT-RAM technologies — i.e., it is high-performance, power-efficient, and scalable. Our evaluation results for a 8-core chip-multiprocessor with 6MB last-level cache show that our proposed design is able to reduce power consumption of a STT-RAM cache by up to 90% (an average of 82%), enhances its lifetime by up to 52% (29% on average), and improves the system performance by up 30% (11% on average), for a wide range of multi-threaded and multi-program workloads.

The failure of Dennard scaling has led to the utilization wall that is the source of dark silicon and limits the percentage of a chip that can actively switch within a given power budget. To address this issue, a structure is needed to guarantee the limited power budget along with providing sufficient flexibility and performance for different applications with various communication requirements. In this article, we present a general-purpose platform for future many-core Chip-Multiprocessors (CMPs) that benefits from the advantages of clustering, Network-on-Chip (NoC) resource sharing among cores, and power gating the unused components of clusters. We also propose two task mapping methods for the proposed platform in which active and dark cores are dispersed appropriately, so that an excess of power budget can be obtained. Our evaluations reveal that the first and second proposed mapping mechanisms respectively reduce the execution time by up to 28.6% and 39.2% and the NoC power consumption by up to 11.1% and 10%, and gain an excess power budget of up to 7.6% and 13.4% over the baseline architecture.

Multi-Level Cell Phase Change Memory (MLC PCM) is a promising candidate technology for DRAM replacement in main memory of modern computers. Despite of its high density and low power advantages, this technology seriously suffers from slow read and write operations. While prior works extensively studied the problem of slow write, this paper targets high read latency problem in MLC PCM and introduces an architecture mechanism to overcome it. To this end, we rely on the fact that reading different bits from an MLC cell takes different latencies, i.e., for a 2-bit MLC, reading its Most-Significant Bit (MSB) is fast, while reading its Least-Significant Bits (LSBs) is slower. We then propose Half-Line PCM (HL-PCM), a novel memory architecture that leverages this non-uniformity in reading MLC PCM's content to send a requested memory block to the processor in different cycles-it sends half of a memory block to the processor ahead of the other half. If the processor requested a word belonging to the first half, it can resume its execution on receiving the first half, while the other half has not sent yet and scheduled to be received by the memory controller later. HL-PCM is easy and simple to implement, i.e., it needs minor modifications at memory controller, the search/evict policies at last level cache, as well as data layout in main memory. Our experimental results show that the proposed design improves the average memory access latency by 33-43 percent and program's execution time by 23 percent, on average, while incurring negligible overhead at memory controller and PCM DIMM, in a 16-core chip multiprocessor (CMP) running memory-intensive benchmarks.

The continuance of Moore's law and failure of Dennard scaling force future chip multiprocessors (CMPs) to have considerable dark regions. How to use up available dark resources is an important concern for computer architects. In harmony with these changes, we must revise processor allocation schemes that severely affect the performance of a parallel on-chip system. A suitable allocation algorithm should reduce runtime and increase the power efficiency with proper thermal distribution to avoid hotspots. With this motivation, this paper proposes a power-efficient and high performance general purpose infrastructure for which a Dark Silicon Aware Processor Allocation (DSAPA) scheme is proposed which targets future many-core systems. To obtain high performance, we suggest a tunable-clustered mesh with the capability of sharing NoC resources in each cluster. We also employ a buffer-level power gating technique is used to improve power efficiency. Evaluation results reveal that the maximum achieved performance and power consumption improvements are 38.7% and 29.4% for multi-threaded workloads over the equivalent conventional design.

Although resistive RAM (ReRAM) technology offers a good combination of high capacity and low-power for cache memories, its long write latency and low endurance are potential showstoppers to its wide commercial adoption. In particular, its low write-endurance can cause fast wear-out of cache lines, bringing reliability issues and leading to capacity reduction over time. This problem is exacerbated when ReRAM cache has dynamic NUCA structure, where each core brings most of its data to the cache banks close to itself and writes become localized. We propose Re-NUCA, a NUCA architecture design for ReRAM cache to address its lifetime problem while keeping its performance high. Re-NUCA relies on performance-wise data criticality: if it realizes a cache line is performance critical, it keeps it in the banks close to the target core, like dynamic NUCA, otherwise, it maps cache lines onto banks using static NUCA to evenly distribute writes over cache banks. This change in mapping of cache lines to banks relaxes the lifetime problem in ReRAM NUCA significantly and wear-levels the lifetime of banks. Re-NUCA needs a logic for detecting performance-wise critical cache lines and a low-overhead changes in TLB for keeping mapping information. Our experimental results of a 16-core chip multiprocessor with 32MB ReRAM L3 cache show that Re-NUCA improves the lifetime of the non-volatile cache by about 42%, on average, with almost no impact on performance.

Despite its promise as a DRAM main memory replacement, Phase Change Memory (PCM) has high write latencies which can be a serious detriment to its widespread adoption. Apart from slowing down a write request, the consequent high latency can also keep other chips of the same rank, that are not involved in this write, idle for long times. There are several practical considerations that make it difficult to allow subsequent reads and/or writes to be served concurrently from the same chips during the long latency write. This paper proposes and evaluates several novel mechanisms - re-constructing data from error correction bits instead of waiting for chips currently busy to serve a read, rotating word mappings across chips of a PCM rank, and rotating the mapping of error detection/correction bits across these chips - to overlap several reads with an ongoing write (RoW) and even a write with an ongoing write (WoW). The paper also presents the necessary micro-architectural enhancements needed to implement these mechanisms, without significantly changing the current interfaces. The resulting PCM access parallelism (PCMap) system incorporating these enhancements, boosts the intra-rank-level parallelism during such writes from a very low baseline value of 2.4 to an average and maximum values of 4.5 and 7.4, respectively (out of a maximum of 8.0), across a wide spectrum of both multiprogrammed and multithreaded workloads. This boost in parallelism results in an average IPC improvement of 15.6% and 16.7% for the multi-programmed and multi-threaded workloads, respectively.

This paper alleviates the problem of slow reads in the Multi-Level Cell Phase Change Memory (MLC PCM) by exploiting a the fact that the Most-Significant Bit (MSB) of MLCs is read fast, while reading the Least-Significant Bits (LSBs) is slower. We propose Half-Line PCM (HL-PCM), a memory architecture that leverages this property to send half of a cache line to the processor ahead of the other half, so that processor continues its execution if the missed data element is in the first half. Our evaluation shows that HL-PCM improves program execution time by 23%, on average, in a 16-core CMP model for workloads from PARSEC-2 benchmark.

The system administrator, faces an arduous task of figuring out whether to consolidate storage workloads, which workloads to isolate, which workloads to co-locate, and how to reduce the interference on co-located workloads? This paper presents an approach to ease this arduous task. We consider different mixes of enterprise storage applications on a high-end SSD to study their performance, system throughput and fairness in their consolidated execution. The paper also considers a static approach using an integrated combination of resource partitioning and data placement to reduce the interference between the workloads.

In the last decade, NAND flash-based SSDs have been widely adopted for high-end enterprise systems in an attempt to provide a high-performance and reliable storage. However, inferior performance is frequently attained mainly due to the need for Garbage Collection (GC). GC in flash memory is the process of identifying and clearing the blocks of unneeded data to create space for the new data to be allocated. GC is a high-latency operation and once it is scheduled for service to a block of a plane in a flash chip (each flash chip consists of multiple planes), it can increase latency for later arriving I/O requests to the same plane. Apart from that, the consequent high latency also keep other planes of the same chip, that are not involved in this GC, idle for a long time. We show that for the baseline SSD with modern FTL, GC considerably reduces the plane-level parallelism, causing significant performance degradation. There are several circuit-level constraints that make it difficult to allow subsequent I/O operations and/or GCs to be served concurrently from the same chip, but different planes, during the long latency GC. This paper proposes a novel GC strategy, called Parallel GC (PaGC), whose goal is to proactively run GC on the remaining planes of a flash chip whenever any of its planes needs to execute on-demand GC. The resulting PaGC system boosts the response time of I/O requests by up to 45% (32% on average) for different GC settings and across a wide spectrum of enterprise I/O workloads.

Phase Change Memory (PCM) devices are one of the known promising technologies to take the place of DRAM devices with the aim of overcoming the obstacles of reducing feature size and stopping ever growing amounts of leakage power. In exchange for providing high capacity, high density, and nonvolatility, PCM Multilevel Cells (MLCs) impose high write energy and long latency. Many techniques have been proposed to resolve these side effects. However, read performance issues are usually left behind the great importance of write latency, energy, and lifetime. In this article, we focus on read performance and improve the critical path latency of the main memory system. To this end, we exploit striping scheme by which multiple lines are grouped and lie on a single MLC line array. In order to achieve more performance gain, an adaptive ordering mechanism is used to sort lines in a group based on their read frequency. This scheme imposes large energy and lifetime overheads due to its intensive demand for higher write bandwidth. Thus, we equipped our design with a grouping/pairing write queue to synchronize write-back requests such that all updates to an MLC array occur at once. The design is also augmented by a directional write scheme that takes benefits of the uniformity of accesses to the PCM device—caused by the large DRAM cache—to determine the writing mode (striped or nonstriped). This adaptation to write operations relaxes the energy and lifetime overheads. We improve the read latency of a 2-bit MLC PCM memory by more than 24% (and Instructions Per Cycle (IPC) by about 9%) and energy-delay product by about 20% for a small lifetime degradation of 8%, on average.

The emergence of new memory technologies provides us with opportunity to enhance the properties of existing memory architectures. One such technology is Phase Change Memory (PCM) which boasts superior scalability, power savings, non-volatility, and a performance competitive to Dynamic Random Access Memory (DRAM). In this paper, we propose a write buffer architecture for Solid-State Drives (SSDs) which attempts to exploit PCM as a DRAM alternative while alleviating its issues such as long write latency, high write energy, and finite endurance. To this end and based on thorough I/O characterization of desktop and enterprise applications, we propose a hybrid DRAM-PCM SSD cache design with an intelligent data movement scheme. This architecture manages to improve energy efficiency while enhancing performance and endurance. To study the design trade-offs between energy, performance, and endurance, we augmented Microsoft's DiskSim SSD model with a detailed hybrid cache using PCM and DRAM parameters from a rigorous survey of device prototypes. We study the design choices of implementing different PCM and DRAM arrays to achieve the best trade-off between energy and performance. The results display up to 77 percent power savings compared to a DRAM cache and up to percent reduction in request response time for a variety of workloads, while greatly improving disk endurance.

Emerging nonvolatile memory technologies, such as spin-transfer torque RAM or resistive RAM, can increase the capacity of the last-level cache (LLC) in a latency and power-efficient manner. These technologies endure 109-1012writes per cell, making a nonvolatile cache (NV-cache) with a lifetime of dozens of years under ideal working conditions. However, nonuniformity in writes to different cache lines considerably reduces the NV-cache lifetime to a few months. Writes to cache lines can be made uniformly by wear-leveling. A suitable wear-leveling for NV-cache should not incur high storage and performance overheads. We propose a novel, simple, and effective wear-leveling technique with negligible performance overhead of <;0.4% for memory-intensive workloads. Our proposal consists of two mechanisms: 1) a wear-leveling mechanism within each cache set that slightly increases main memory write-back traffic and LLC miss rate and 2) a novel technique to reduce cache interset variation which causes minimum interference with normal cache operation. Using these mechanisms, we show that the lifetime of the NV-cache is boosted up to 13× for different cache configurations.

With current memory scalability challenges, Phase-Change Memory (PCM) is viewed as an attractive replacement to DRAM. The preliminary concern for PCM applicability is its limited write endurance that results in fast wear-out of memory cells. Worse, process variation in the deep-nanometer regime increases the variation in cell lifetime, resulting in an early and sudden reduction in main memory capacity due to the wear-out of a few cells. Recent studies have proposed redirection or correction schemes to alleviate this problem, but all suffer poor throughput or latency. In this article, we show that one of the inefficiency sources in current schemes, even when wear-leveling algorithms are used, is the nonuniform write endurance limit incurred by process variation, that is, when some memory pages have reached their endurance limit, other pages may be far from their limit. In this line, we present a technique that aims to displace a faulty page to a healthy page. This technique, called On-Demand Page Paired PCM (OD3P, for short), when applied at page level, can improve PCM time-to-failure by 20% on average for different multithreaded and multiprogrammed workloads while also improving IPC by 14% on average compared to previous page-level techniques. The comparison between line-level OD3P and previous line-level techniques reveals about 2× improvement of lifetime and performance.

Future GPUs should have larger L2 caches based on the current trends in VLSI technology and GPU architectures toward increase of processing core count. Larger L2 caches inevitably have proportionally larger power consumption. In this article, having investigated the behavior of GPGPU applications, we present an efficient L2 cache architecture for GPUs based on STT-RAM technology. Due to its high-density and low-power characteristics, STT-RAM technology can be utilized in GPUs where numerous cores leave a limited area for on-chip memory banks. They have, however, two important issues, high energy and latency of write operations, that have to be addressed. Low retention time STT-RAMs can reduce the energy and delay of write operations. Nevertheless, employing STT-RAMs with low retention time in GPUs requires a thorough study on the behavior of GPGPU applications. Based on this investigation, we have architectured a two-part STT-RAM-based L2 cache with low-retention (LR) and high-retention (HR) parts. The proposed two-part L2 cache exploits a dynamic threshold regulator (DTR) to efficiently regulate the write threshold for migration of the data blocks from HR to LR, based on the behavior of the applications. Also, a Data and Access type Aware Cache Search mechanism (DAACS) is hired for handling the search of the requested data blocks in two parts of the cache. The STT-RAM L2 cache architecture proposed in this article can improve IPC by up to 171% (20% on average), and reduce the average consumed power by 28.9% compared to a conventional L2 cache architecture with equal on-chip area.

Phase change memory (PCM) has rapidly progressed and surpassed dynamic random-access memory in terms of scalability and standby energy efficiency. While PCM cell size is marching toward the minimum achievable feature size, recent prototypes effectively improve device scalability by storing multiple bits per cell. Unfortunately, the density advantage of multilevel cell (MLC) PCM devices comes at the cost of higher latency and energy consumption as well as low resilience to soft errors because of resistance drift. To address these challenges, we propose variable resistance spectrum MLC PCM (VR-PCM), a simple microarchitectural technique to handle main memory access mechanisms with more efficient drift-aware MLC PCM access operations. VR-PCM relies on the observation that data patterns at various granularities are nonuniformly distributed across memory transactions when running various workloads. Motivated by this observation, VR-PCM reconfigures PCM resistance spectrum partitioning into nonuniform regions that are then assigned to the binary data patterns based on their occurrence frequency. Using full-system evaluation of an MLC PCM main memory with conservative resistance drift model, we show that VR-PCM tailored for high-density MLCs delivers considerable improvements in performance (13.25%), energy (21.2%), and lifetime (1.77 x ), on average.

Solid State Drives (SSDs) have recently emerged as a high speed random access alternative to classical magnetic disks. To date, SSD designs have been largely based on multi-channel bus architecture that confronts serious scalability problems in high-end enterprise SSDs with dozens of flash memory chips and a gigabyte host interface. This forces the community to rapidly change the bus-based inter-flash standards to respond to ever increasing application demands. In this paper, we first give a deep look at how different flash parameters and SSD internal designs affect the actual performance and scalability of the conventional architecture. Our experiments show that SSD performance improvement through either enhancing intra-chip parallelism or increasing the number of flash units is limited by frequent contentions occurred on the shared channels. Our discussion will be followed up by presenting and evaluating a network-based protocol adopted for flash communications in SSDs that addresses design constraints of the multi-channel bus architecture. This protocol leverages the properties of interconnection networks to attain a high performance SSD. Further, we will show and discuss that using this communication paradigm not only helps to obtain better SSD backend latency and throughput, but also to lower the variance of response time compared to the conventional designs. In addition, greater number of flash chips can be added with much less concerns on board-level signal integrity challenges including channels' maximum capacitive load, output drivers' slew rate, and impedance control.

With current memory scalability challenges, Phase Change Memory (PCM) is viewed as an attractive replacement to DRAM. The preliminary concern for PCM applicability is its limited write endurance that is highly affected by process variation in nanometer regime. This increases the variation in cell lifetime resulting in early and sudden reduction in main memory capacity due to wear-out of few cells. When some memory pages reach their endurance limits, other pages may be far from their limits even when using a perfect wear-leveling. Recent studies have proposed redirection or correction schemes to alleviate this problem, but all suffer from poor throughput or latency. On contrary, we present On-Demand Page Paired PCM (OD3P), a technique that mitigates the problem of fast failure of pages by redirecting them onto other healthy pages, leading to gradual capacity degradation. Compared to a state-of-the-art error correction scheme for PCM, our experiments indicated that OD3P can improve PCM time-to-failure and system performance (IPC) by 12% and 14%, respectively, under multi-threaded and multi-programmed workloads.

In this paper, having investigated the behavior of GPGPU applications, we present an efficient L2 cache architecture for GPUs based on STT-RAM technology. With the increase of processing cores count, larger on-chip memories are required. Due to its high density and low power characteristics, STT-RAM technology can be utilized in GPUs where numerous cores leave a limited area for on-chip memory banks. They have however two important issues, high energy and latency of write operations, that have to be addressed. Low data retention time STT-RAMs can reduce the energy and delay of write operations. However, employing STT-RAMs with low retention time in GPUs requires a thorough investigation on the behavior of GPGPU applications based on which the STT-RAM based L2 cache is architectured. The STT-RAM L2 cache architecture proposed in this paper, can improve IPC by more than 100% (16% on average) while reducing the average consumed power by 20% compared to a conventional L2 cache architecture with equal on-chip area.

In this paper, we study the problem of resistance drift in an MLC Phase Change Memory (PCM) and propose a solution to circumvent its thermally-affected accelerated rate in 3D CMPs. Our scheme is based on the observation that instead of alleviating the problem of resistance drift by using large margins or error correction codes, the PCM read circuit can be reconfigured for tolerating most of the resistance drift errors in a dynamic manner. Through detailed characterization of memory access patterns for 22 applications, we propose an efficient mechanism to facilitate such reliable read scheme via tolerating (a) early-cycle resistance drifts by using narrow margins so that considerably saving energy of writes and improving cell endurance, and (b) late-cycle resistance drifts by accurately estimating resistance thresholds that separate states for sensing. Evaluations on a true 3D architecture, consisting of a 4-core CMP and a banked 2-bit PCM memory, show that our proposal provides 106× lower error rate compared to the state-of-the-art designs of PCMs.

Although phase change memory with multi-bit storage capability (known as MLC PCM) offers a good combination of high bit-density and non-volatility, its performance is severely impacted by the increased read/write latency. Regarding read operation, access latency increases almost linearly with respect to cell density (the number of bits stored in a cell). Since reads are latency critical, they can seriously impact system performance. This paper alleviates the problem of slow reads in the MLC PCM by exploiting a fundamental property of MLC devices: the Most-Significant Bit (MSB) of MLC cells can be read as fast as SLC cells, while reading the Least-Significant Bits (LSBs) is slower. We propose Striped PCM (SPCM), a memory architecture that leverages this property to keep MLC read latency in the order of SLC's. In order to avoid extra writes onto memory cells as a result of striping memory lines, the proposed design uses a pairing write queue to synchronize write-back requests associated with blocks that are paired in striping mode. Our evaluation shows that our design significantly improves the average memory access latency by more than 30% and IPC by up to 25% (10%, on average), with a slight overhead in memory energy (0.7%) in a 4-core CMP model running memory-intensive benchmarks.

Network-on-Chip (NoC) paradigm has emerged as a revolutionary methodology to integrate numerous IP blocks on a single chip. The achievable performance of adopting NoCs is constrained by the performance limitation mainly imposed by the metal wires that are the physical realization of communication channels. According to the International Technology Roadmap for Semiconductors (ITRS) report, new interconnect paradigms providing huge bandwidth is in need for future products. The current wired channels have limited bandwidth, and consequently, they limit the performance enhancements that NoC architectures can provide. Optical interconnects are capable of achieving better performance via high-speed high-bandwidth point-to-point connections, if their cost overhead can be mitigated. In this paper, we evaluate the performance of opto-electrical multistage NoC architectures which use a sample-based flow prediction method at hardware level with minimum communication and area overhead to predict heavily communicating flows. Our evaluation of the proposed structure demonstrates its superior functionality in terms of throughput, latency, and energy dissipation with respect to traditional NoC architectures.

In Solid-State Drives (SSDs) with tens of flash chips and highly parallel architecture, we can speed up I/O operations by well-utilizing resources during page allocation. Proposals already exist for using static page allocation which does not balance the IO load and its efficiency depends on access address patterns. To our best knowledge, there have been no research thus far to show what happens if one or more internal resources can be freely allocated regardless of the request address. This paper explores the possibility of using different degrees of dynamism in page allocation and identifies key design opportunities that they present to improve SSD's characteristics.

Programmable hardware is gaining popularity as it can keep pace with growing performance demand in tight power budget, design and test cost, and serious reliability concerns of future multiprocessor embedded systems. Compatible with this trend, Network-on-Chip, as a potential bottleneck of future multi-cores, should also support programmability. Here, we address this issue in design and implementation of routing algorithm for two-dimensional mesh. To this end, we allocate paths based on input traffic pattern and in parallel with customizing routing restriction for deadlock freedom. To achieve this, we propose extended turn model (ETM), a novel parametric deadlock-free routing for 2D meshes that generalize prior turn-based routing methods (e.g., odd-even) with great degree of freedoms. This model facilitates design of Mixed-Integer Linear Programming (MILP) approach, which considers channel dependency turns as independent variables and decides for both path allocation and routing restriction. We solve this problem by genetic algorithm and evaluate it using simulation experiments. Results reveal that application-aware ETM-based path allocation outperforms prior turn-based approaches under synthetic and real traffic loads.

Phase Change Memory (PCM) is emerging as a high-dense and power-efficient choice for future main memory systems. While PCM cell size is marching towards minimum achievable feature size, recent prototypes effectively improve device scalability by storing multiple bits per each cell. Unfortunately, Multi-Level Cell (MLC) PCM devices offer higher access time and energy when compared to Single-Level Cell (SLC) counterparts making it difficult to incorporate MLC in main memory. To address this challenge, we proposes Zero-value-based Morphable PCM, ZM-PCM for short, a novel MLC-PCM main memory architecture which tries incorporating benefits of both MLC and SLC devices within the same structure. ZM-PCM relies on the observation that zero value at various granularities is frequently occurred within main memory transactions when running PARSEC-2 programs. Motivated by this observation, ZM-PCM codes redundant zero MLC cells into limited bits that is storable in the SLC (or alternatively in devices with fewer bits) form with improved latency, energy, and lifetime with no reduction in available main memory capacity. We evaluate microarchitecture design of morphable PCM cell, coding and decoding algorithms and details of related circuits. We also introduce a simple area-efficient caching mechanism for fast cost-efficient access to coding metadata. Our evaluation on a quad-core CMP with 4GB 8-bit MLC PCM main memory shows that ZM-PCM morphs up to 93% (and 50% on average) of all memory cells with lower densities which directly turns in performance, power and lifetime enhancement.

Networks-on-Chip (NoCs for short) are known as the most scalable and reliable on-chip communication architectures for multi-core SoCs with tens to hundreds IP cores. Proper mapping the IP cores on NoC tiles (or assigning threads to cores in chip multiprocessors) can reduce end-to-end delay and energy consumption. While almost all previous works on mapping consider higher priority for the application's flows with higher required bandwidth, a mapping strategy, presented in this paper, is introduced that considers multicast communication flows in addition to the normal unicast flows. To this end, multicast and unicast traffic flows are first characterized in terms of some new metrics which are then used for arranging communication flows based on their volume and priority. A heuristic approach is used to assign IP cores to NoC tiles. Simulation results for both synthetic and real applications show up to 49% (28% on average) performance improvement and 44% (22% on average) energy saving when compared to the best known mapping algorithm, nMap.

End-to-end delay, throughput, energy consumption, and silicon area are the most important design metrics of networks-on-chip (NoCs). Although several analytical models have been previously proposed for predicting such metrics in NoCs, very few of them consider the effect of message waiting time in the buffers of network routers for predicting overall power consumptions and none of them consider structural heterogeneity of network routers. This paper introduces two inter-related analytical models to compute message latency and power consumption of NoCs with arbitrary topology, buffering structure, and routing algorithm. Buffer allocation scheme defines the buffering space for each individual channel of the NoC that can be homogenous (all channels having similar buffer structures) or heterogeneous (each channel having its own buffer structure). Here, the buffer allocation scheme can be either homogenous or heterogeneous. We assume no bandwidth sharing of virtual channels for a physical channel, and IP cores generate messages following a Poisson distribution. The results obtained from simulation experiments confirm that the proposed models exhibit acceptable accuracy for different network configurations operating under various working conditions. We have shown that basing our analysis on a Poisson traffic model is still useful for scenarios with real application workloads.

Although several analytical models have been proposed for wireless sensor networks (WSNs) with different capabilities, very few of them consider the effect of general service distribution as well as design constraints on network performance. This paper presents a new analytical model to compute message latency in a WSN with loop-free Bellman Ford routing strategy. The model considers limited buffer size for each node using M/G/1/k queuing system. Also, contention probability and resource utilization are suitably modeled. The results obtained from simulation experiments confirm that the model exhibits a high degree of accuracy for various network configurations.

In this paper, we propose a novel on-chip communication scheme by dividing the resources of a traditional packet-switched network-on-chip between a packet-switched and a circuit-switched sub-network. The former directs packets according to the traditional packet-switching mechanism, while the latter forwards packets over circuits which are directly established between two non-adjacent nodes by bypassing the intermediate routers. A packet may switch between the sub-networks several times to reach its destination. The circuits are set up using a low-latency and low-cost setup-network. The network resources are split between the two sub-networks using Spatial-Division Multiplexing (SDM). The work aims to improve the power and performance metrics of Network-on-Chip (NoC) architectures and benefits from the power and scalability advantage of packet-switched NoCs and superior communication performance of circuit-switching. The evaluation results show a significant reduction in power and latency over a traditional packet-switched NoC.

Large Multi-Processor Systems-on-Chip use Networks-on-Chip with a high degree of reusability and scalability for message communication. Therefore, network infrastructure is a crucial element affecting the overall system performance. On the other hand, technology improvements may lead to much energy consumption in micro-routers of an on-chip network. This necessitates an exhaustive analysis of NoCs for future designs. This paper presents a comprehensive analytical model to predict message latency for different data flows traversing across the network. This model considers channel buffers of multiple flits which were not previously studied in NoC context. Also, architectural descriptions of the overall consumed power in the network components are extracted considering message arrival and service rates. The results obtained from simulation experiments confirm that the proposed performance and power models exhibit good accuracy for various network configurations and workloads.