Data allocation and migration for Beidou navigation terminals with hybrid PCM main memory

This research proposes a phase-change memory (PCM) based main memory system with an effective combination of a superblock-based adaptive buffering structure and its associated set divisible last-level cache (LLC). To achieve high performance similar to that of dynamic random-access memory (DRAM) based main memory, the superblock-based adaptive buffer (SABU) is comprised of dual DRAM buffers, i.e., an aggressive superblock-based pre-fetching buffer (SBPB) and an adaptive sub-block reusing buffer (SBRB), and a set divisible LLC based on a cache space optimization scheme. According to our experiment, the longer PCM access latency can typically be hidden using our proposed SABU, which can significantly reduce the number of writes over the PCM main memory by 26.44%. The SABU approach can reduce PCM access latency up to 0.43 times, compared with conventional DRAM main memory. Meanwhile, the average memory energy consumption can be reduced by 19.7%.

Phase-Change Memory (PCM) has emerged as a promising low-power candidate to replace DRAM in main memory. Hybrid memory architecture comprised of a large PCM and a small DRAM is a popular solution to mitigate undesirable characteristics of PCM writes. Because PCM writes are much slower than reads, writebacks from the last-level cache consume a large portion of memory bandwidth, and thus, impact performance. Effectively utilizing shared resources, such as the last-level cache and the memory bandwidth, is crucial to achieving high performance for multi-core systems. Although existing memory bandwidth allocation schemes improve system performance, no current approach uses writeback information to partition bandwidth for hybrid memory. We use a writeback-aware analytic model to derive the allocation strategy for bandwidth partitioning of phase-change memory. From the derivation of the model, Writeback-aware Bandwidth Partitioning (WBP) is proposed as a new runtime mechanism to partition PCM service cycles among applications. WBP uses a partitioning weight to indicate the importance of writebacks (in addition to LLC misses) to bandwidth allocation. A companion Dynamic Weight Adjustment (DWA) scheme dynamically selects the partitioning weight to maximize system performance. Simulation results show that WBP and DWA improve performance by 24.9% (weighted speedup) over bandwidth partitioning schemes that do not take writebacks into consideration in a 8-core system.

Phase Change Memory (PCM) is emerging as one of the most promising alternative technology to the Dynamic RAM (DRAM) when building large-scale main memory systems. Even though the PCM is easy to scale, it encounters serious endurance problems. Writes are the primary wear mechanism in the PCM. The PCM can perform 108 to 109 times of writes before it cannot be programmed reliably. In addition, the PCM has high write latency. To prolong the lifetime of the PCM as the main memory and enhance the performance, we propose a Scratch Pad Memory (SPM) based memory mechanism and an Integer Linear Programming (ILP) memory activities scheduling algorithm to reduce the redundant write operations in the PCM. The idea of our approach is to share the data copies among the SPMs, instead of writing back to the PCM main memory each time a modify occurs. Our experimental results show that the ILP scheduling can generate the optimal schedule of memory activities with minimum write operations, reducing the number of write by up to 61%.

This research aims to design a new phase-change RAM (PRAM)-based main memory structure, supporting the advantages of PRAM while providing performance similar to that of conventional DRAM main memory. To replace conventional DRAMs with non-volatile PRAMs as the main memory components, comparable memory access latency, overall cost, power dissipation, and memory cell endurance should be supported. For these goals, we propose a new main memory system consisting of a DRAM converter and an array of single-level cell (SLC)/multi-level cell (MLC) PRAMs. The DRAM converter consists of an aggressive fetching superblock buffer to assure better use of spatial locality and a selective filtering buffer for better use of temporal locality. The array of the SLC/MLC hybrid PRAM structure includes a combination of SLC and MLC PRAMs to enhance the lifetime of the MLC PRAM main memory and hide asymmetric read/write access latency. The proposed structure is evaluated by a trace-driven simulator using SPEC CPU 2006 and SPLASH-2 traces. Experimental results show that the proposed DRAM converter can reduce the miss rate by ∼37% and write count by ∼55% in comparison with the uniform buffer case. Also, the SLC/MLC PRAM with DRAM converter shows performance in terms of access latency and power consumption close to that of the conventional memory architecture. Thus, our proposed memory architecture can be used to replace the current DRAM-based main memory system.

Phase change random access memory (PRAM) is one kind of nonvolatile memory, which is desirable to be used for DSP systems as main memory, as it consumes less power than DRAM and is much denser than DRAM. In this paper, we utilize a hybrid main memory composed of DRAM and PRAM, which leverages the low power consumption of PRAM while minimizing the performance and lifetime degradation caused by PRAM write. To make full use of different advantages of DRAM and PRAM, especially for the application-specific DSP systems, we reconsider the variable partitioning and instruction scheduling problems on the hybrid main memory. Different optimization objectives, for example power consumption, schedule length, and the number of writes on PRAM, are considered. At the same time, different kinds of hybrid architectures are analyzed. Graph models, ILP model, and algorithms are proposed for different settings. Experiments show that the proposed techniques reduce up to 49% power consumption and 88% the number of writes on PRAM on average.

Using nonvolatile memories in memory hierarchy has been investigated to reduce its energy consumption because nonvolatile memories consume zero leakage power in memory cells. One of the difficulties is, however, that the endurance of most nonvolatile memory technologies is much shorter than the conventional SRAM and DRAM technology. This has limited its usage to only the low levels of a memory hierarchy, e.g., disks, that is far from the CPU.

Phase change memory (PCM) is considered as a promising alternative of DRAM-based main memory in embedded systems. A PCM cell can be dynamically programmed to be in either multiple-level cell (MLC) mode or single-level cell (SLC) mode. With this morphable feature, we can utilize the high-density of MLC and low-latency of SLC, to satisfy various memory requirements of specific applications in embedded systems. However, compared to its SLC counterpart, the lifetime of MLC is limited. In particular, a program in embedded systems usually exhibits an extremely unbalanced write pattern, which may accelerate the wear-out of MLC cells in morphable PCM. To address this issue, this paper proposes a simple and effective wear-leveling technique, named Mixer, to enhance the lifetime of morphable PCM considering the program specific features. We first build an Integer Linear Programming (ILP) formulation to produce optimal SLC/MLC partition and data allocation, to achieve a balanced write distribution in morphable PCM with low memory access cost. The basic idea is to allocate fast SLC and MLC cells for write intensive variables and other ordinary variables, respectively. We then propose a polynomial time algorithm to achieve near-optimal results. The evaluation results show that the proposed technique can effectively extend the lifetime of morphable PCM in embedded systems compared with previous work.

Phase Change Memory (PCM) is an emerging Non Volatile Memory (NVM) technology that has the potential to provide scalable high-density memory systems. While the non-volatility of PCM is a desirable property in order to save leakage power, it also has the undesirable effect of making PCM main memories susceptible to newer modes of security vulnerabilities, for example, accessibility to sensitive data if a PCM DIMM gets stolen. PCM memories can be made secure by encrypting the data. Unfortunately, such encryption comes with a significant overhead in terms of bits written to PCM memory, causing half of the bits in the line to change on every write, even if the actual number of bits being written to memory is small. Our studies show that a typical writeback modifies, on average, only 12% of the bits in the cacheline. Thus, encryption causes almost a 4x increase in the number of bits written to PCM memories. Such extraneous bit writes cause significant increase in write power, reduction in write endurance, and reduction in write bandwidth. To provide the benefit of secure memory in a write efficient manner this paper proposes Dual Counter Encryption (DEUCE). DEUCE is based on the observation that a typical writeback only changes a few words, so DEUCE reencrypts only the words that have changed. We show that DEUCE reduces the number of modified bits per writeback for a secure memory from 50% to 24%, which improves performance by 27% and increases lifetime by 2x.

Phase change memory (PCM) is non-volatile memory that is byte-addressable. It is two to four times denser than DRAM, orders of magnitude better than NAND Flash memory in read latency, and 10 times better than NAND Flash memory in write endurance. However, it still limits the number of write operations to at most 106 times per PCM cell. To extend its lifetime, it is necessary to evenly distribute write operations over all the memory cells. Up to now, the B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree index structure has been used to quickly locate a search key in a relational database management system (RDBMS). All the record keys in each node are sorted and packed upon insertion in, and deletion from, the B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree. In addition, a counter keeps track of the number of valid keys in the B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree. Consequently, a B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree algorithm results in a large number of write operations, which deteriorates the endurance of PCM. This restricts the usage of PCM on a database server and deteriorates performance of database servers. In this paper, we propose a novel PCM-aware B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree index structure, called PB <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree, to provide wear-leveling in PCM. According to our experiment results, PB <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree is much faster than the existing B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree algorithms for PCM and NAND Flash memory with versatile workloads. More importantly, our scheme also greatly reduces the number of write operations compared to other B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree algorithms. All of these results suggest that PB <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree is the B <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> -Tree algorithm best fitted to PCM.

Phase change memory (PCM) is known for its potentials as main memory and as storage. In contrast to the past work, this work presents a PCM translation layer that considers how the main memory is used by the operating system together with the usage patterns of storage by trading their performance and reliability. In particular, a joint management scheme is proposed to improve the capability of PCM as both main memory and storage so as to enhance the performance of the entire system. The endurance issue of PCM for main memory is resolved by utilizing the potentially large capacity of the PCM storage space with limited modifications to the existing operating system implementations. Moreover, three commands are proposed to help operating system engineers to take advantage of PCM as main memory and storage by reducing I/O overheads and speeding up both the initialization and termination of program executions. The experimental results show that the performance of PCM as both main memory and storage can be significantly improved with reasonable lifetime, while the system overhead is very limited under coarse-grained wear leveling.

Green cloud is an emerging new technology in the computing world in which memory is a critical component. Phase-change memory (PCM) is one of the most promising alternative techniques to the dynamic random access memory (DRAM) that faces the scalability wall. Recent research has been focusing on the multi-level cell (MLC) of PCM. By precisely arranging multiple levels of resistance inside a PCM cell, more than one bit of data can be stored in one single PCM cell. However, the MLC PCM suffers from the degradation of performance compared to the single-level cell (SLC) PCM, due to the longer memory access time. In this paper, we present a genetic-based optimization algorithm for chip multiprocessor (CMP) equipped with PCM memory in green clouds. The proposed genetic-based algorithm not only schedules and assigns tasks to cores in the CMP system, but also provides a PCM MLC configuration that balances the PCM memory performance as well as the efficiency. The experimental results show that our genetic-based algorithm can significantly reduce the maximum memory usage by 76.8 percent comparing with the uniform SLC configuration, and improve the efficiency of memory usage by 127 percent comparing with the uniform 4 bits/cell MLC configuration. Moreover, the performance of the system is also improved by 24.5 percent comparing with the uniform 4 bits/cell MLC configuration in terms of total execution time.

PCM (phase change memory) has been regarded as one of the most promising NVRAM. Due to its excellent features including high access speed, good scalability, byte addressability, and low idle power, PCM is expected to be an alternative to DRAM or flash memory in the future. So far, many different kinds of architecture have been proposed to merge PCM into the memory hierarchy of computer systems. For PCM-based computer systems, considering that PCM has various properties differing with DRAM and conventional storage media, traditional cache management policies based on DRAM and disks have to be re-designed. In this paper, we present a survey on the cache management policies for PCM-based systems that employ PCM as main memory or as secondary storage. Specially, for different PCM-based architectures, we explain how PCM-aware cache management policies exploit PCM’s advantages and overcome PCM’s drawbacks like asymmetric read/write latencies.

Phase-Change Memory (PCM) has emerged as a promising low-power main memory candidate to replace DRAM. The main problems of PCM are that writes are much slower and more power hungry than reads, write bandwidth is much lower than read bandwidth, and limited write endurance. Adding an extra layer of cache, which is logically the last-level cache (LLC), can mitigate the drawbacks of PCM. However, writebacks from the LLC might (a) overwhelm the limited PCM write bandwidth and stall the application, (b) shorten lifetime, and (c) increase energy consumption. Cache partitioning and replacement schemes are important to achieve high throughput for multi-core systems. However, we noted that no existing partitioning and replacement policy takes into account the writeback information. This paper proposes two writeback-aware schemes to manage the LLC for PCM main memory systems. Writeback-aware Cache Partitioning (WCP) is a runtime mechanism that partitions a shared LLC among multiple applications. Unlike past partitioning schemes, our scheme considers the reduction in cache misses as well as writebacks. Write Queue Balancing (WQB) replacement policy manages the cache partition of each application intelligently so that the writebacks are distributed evenly among PCM write queues. In this way, applications rarely stall due to unbalanced PCM write traffic among write queues. Our evaluation shows that WCP and WQB result in, on average, 21% improvement in throughput, 49% reduction in PCM writes, and 14% reduction in energy over a state-of-the-art cache partitioning scheme.

Write bandwidth is an inherent performance bottleneck for Phase Change Memory (PCM) for two reasons. First, PCM cells have long programming time, and second, only a limited number of PCM cells can be programmed concurrently due to programming current and write circuit constraints,For each PCM write, the data bits of the write request are typically mapped to multiple cell groups and processed in parallel. We observed that an unbalanced distribution of modified data bits among cell groups significantly increases PCM write time and hurts effective write bandwidth. To address this issue, we first uncover the cyclical and cluster patterns for modified data bits. Next, we propose double XOR mapping (D-XOR) to distribute modified data bits among cell groups in a balanced way. D-XOR can reduce PCM write service time by 45% on average, which increases PCM write throughput by 1.8x. As error correction (redundant bits) is critical for PCM, we also consider the impact of redundancy information in mapping data and error correction bits to cell groups. Our techniques lead to a 51% average reduction in write service time for a PCM main memory with ECC, which increases IPC by 12%.

Write bandwidth is an inherent performance bottleneck for Phase Change Memory (PCM) for two reasons. First, PCM cells have long programming time, and second, only a limited number of PCM cells can be programmed concurrently due to programming current and write circuit constraints, For each PCM write, the data bits of the write request are typically mapped to multiple cell groups and processed in parallel. We observed that an unbalanced distribution of modified data bits among cell groups significantly increases PCM write time and hurts effective write bandwidth. To address this issue, we first uncover the cyclical and cluster patterns for modified data bits. Next, we propose double XOR mapping (D-XOR) to distribute modified data bits among cell groups in a balanced way. D-XOR can reduce PCM write service time by 45% on average, which increases PCM write throughput by 1.8x. As error correction (redundant bits) is critical for PCM, we also consider the impact of redundancy information in mapping data and error correction bits to cell groups. Our techniques lead to a 51% average reduction in write service time for a PCM main memory with ECC, which increases IPC by 12%.