1,303 research outputs found
Bit-Write-Reducing and Error-Correcting Code Generation Methods for Non-Volatile Memories
早大学位記番号:新8124早稲田大
High-Performance Energy-Efficient and Reliable Design of Spin-Transfer Torque Magnetic Memory
In this dissertation new computing paradigms, architectures and design philosophy are proposed and evaluated for adopting the STT-MRAM technology as highly reliable, energy efficient and fast memory. For this purpose, a novel cross-layer framework from the cell-level all the way up to the system- and application-level has been developed. In these framework, the reliability issues are modeled accurately with appropriate fault models at different abstraction levels in order to analyze the overall failure rates of the entire memory and its Mean Time To Failure (MTTF) along with considering the temperature and process variation effects. Design-time, compile-time and run-time solutions have been provided to address the challenges associated with STT-MRAM. The effectiveness of the proposed solutions is demonstrated in extensive experiments that show significant improvements in comparison to state-of-the-art solutions, i.e. lower-power, higher-performance and more reliable STT-MRAM design
Enabling Recovery of Secure Non-Volatile Memories
Emerging non-volatile memories (NVMs), such as phase change memory (PCM), spin-transfer torque RAM (STT-RAM) and resistive RAM (ReRAM), have dual memory-storage characteristics and, therefore, are strong candidates to replace or augment current DRAM and secondary storage devices. The newly released Intel 3D XPoint persistent memory and Optane SSD series have shown promising features. However, when these new devices are exposed to events such as power loss, many issues arise when data recovery is expected. In this dissertation, I devised multiple schemes to enable secure data recovery for emerging NVM technologies when memory encryption is used. With the data-remanence feature of NVMs, physical attacks become easier; hence, emerging NVMs are typically paired with encryption. In particular, counter-mode encryption is commonly used due to its performance and security advantages over other schemes (e.g., electronic codebook encryption). However, enabling data recovery in power failure events requires the recovery of security metadata associated with data blocks. Naively writing security metadata updates along with data for each operation can further exacerbate the write endurance problem of NVMs as they have limited write endurance and very slow write operations. Therefore, it is necessary to enable the recovery of data and security metadata (encryption counters) but without incurring a significant number of writes. The first work of this dissertation presents an explanation of Osiris, a novel mechanism that repurposes error correcting code (ECC) co-located with data to enable recovery of encryption counters by additionally serving as a sanity-check for encryption counters used. Thus, by using a stop-loss mechanism with a limited number of trials, ECC can be used to identify which encryption counter that was used most recently to encrypt the data and, hence, allow correct decryption and recovery. The first work of this dissertation explores how different stop-loss parameters along with optimizations of Osiris can potentially reduce the number of writes. Overall, Osiris enables the recovery of encryption counters while achieving better performance and fewer writes than a conventional write-back caching scheme of encryption counters, which lacks the ability to recover encryption counters. Later, in the second work, Osiris implementation is expanded to work with different counter-mode memory encryption schemes, where we use an epoch-based approach to periodically persist updated counters. Later, when a crash occurs, we can recover counters through test-and-verification to identify the correct counter within the size of an epoch for counter recovery. Our proposed scheme, Osiris-Global, incurs minimal performance overheads and write overheads in enabling the recovery of encryption counters. In summary, the findings of the present PhD work enable the recovery of secure NVM systems and, hence, allows persistent applications to leverage the persistency features of NVMs. Meanwhile, it also minimizes the number of writes required in meeting this crash consistency requirement of secure NVM systems
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Building Reliable Software for Persistent Memory
Persistent memory (PMEM) technologies preserve data across power cycles and provide performance comparable to DRAM. In emerging computer systems, PMEM will operate on the main memory bus, becoming byte-addressable and cache-coherent. One key feature enabled by persistent memory is to allow software directly accessing durable data using the CPU’s load/store instructions, even from the user-space.However, building reliable software for persistent memory faces new challenges from two aspects: crash consistency and fault tolerance. Maintaining crash consistency requires the ability to recover data integrity in the event of system crashes. Using load/store instructions to access durable data introduces a new programming paradigm, that is prone to new types of programming errors. Fault tolerance involves detecting and recovering from persistent memory errors, including memory media errors and scribbles from software bugs. With direct access, file systems and user-space applications have to explicitly manage these errors, instead of relying on convenient functions from lower I/O stacks.We identify unique challenges in improving reliability for PMEM-based software and propose solutions. The thesis first introduces NOVA-Fortis, a fault-tolerant PMEM file system incorporating replication, checksums, and parity for protecting the file system’s metadata and the user’s file data. NOVA-Fortis is both fast and resilient in the face of corruption due to media errors and software bugs.NOVA-Fortis only protects file data via the read() and write() system calls. When an application memory-maps a PMEM file, NOVA-Fortis has to disable file data protection because mmap() leaves the file system unaware of updates made to the file. For protecting memory-mapped PMEM data, we present Pangolin, a fault-tolerant persistent object library to protect an application’s objects from persistent memory errors.Writing programs to ensure crash consistency in PMEM remains challenging. Recovery bugs arise as a new type of programming error, preventing a post-crash PMEM file from recovering to a consistent state. Thus, we design two debugging tools for persistent memory programming: PmemConjurer and PmemSanitizer. PmemConjurer is a static analyzer using symbolic execution to find recovery bugs without running a compiled program. PmemSanitizer contains compiler instrumentation and run-time recovery bug analysis, compensating PmemConjurer with multi-threading support and store reordering tests
Secure, Reliable, and Energy-efficient Phase Change Main Memory
Recent trends in supercomputing, shared cloud computing, and “big data” applications are placing ever-greater demands on computing systems and their memories. Such applications can readily saturate memory bandwidth, and often operate on a working set which exceeds the capacity of modern DRAM packages. Unfortunately, this demand is not matched by DRAM technology development. As Moore’s Law slows and Dennard Scaling stops, further density improvements in DRAM and the underlying semiconductor devices are difficult [1]. In anticipation of this limitation, researchers have pursued emerging memory technologies that promise higher density than conventional DRAM devices. One such technology in phase-change memory (PCM) is especially desirable due to its increased density relative to DRAM. However, this nascent memory has outstanding challenges to overcome before it is viable as a DRAM replacement. PCM devices have limited write endurance, and can consume more energy than their DRAM counterparts, necessitating careful control of how and how often they are written. A second challenge is the non-volatile nature of PCM devices; many applications rely on the volatility of DRAM to protect security critical applications and operating system address space between accesses and power cycles. An obvious solution is to encrypt the memory, but the effective randomization of data is at odds with techniques which reduce writes to the underlying memory. This body of work presents three contributions for addressing all challenges simultaneously under the assumption that encryption is required. Using an encryption and encoding technique called CASTLE & TOWERs, PCM can be employed as main memory with up to 30× improvement in device lifetime while opportunistically reducing dynamic energy. A second technique called MACE marries encoding and traditional error-correction schemes providing up to 2.6× improvement in device lifetime alongside a whole-lifetime energy evaluation framework to guide system design. Finally, an architecture called WINDU is presented which supports the application of encoding for an emerging encryption standard with an eye on energy efficiency. Together, these techniques advance the state-of-the-art, and offer a significant step toward the adoption of PCM as a main memory
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