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1. Optimizing Persistent Memory Transactions

   https://doi.org/10.1109/PACT.2019.00025  

   Zardoshti, Pantea; Zhou, Tingzhe; Liu, Yujie; Spear, Michael (September 2019, 28th International Conference on Parallel Architectures and Compilation Techniques)

   null (Ed.)

   Byte-addressable, non-volatile, random access memory (NVM) has the potential to dramatically accelerate the performance of storage-intensive workloads. For applications with irregular data access patterns, and applications that rely on ad-hoc data structures, the most promising model for interacting with NVM is a transactional model. However, the specifics of the model matter significantly. We introduce two models for programming persistent transactions. We show how to build concurrent persistent transactional memory from traditional software transactional memories. We then introduce general and model-specific optimizations that can substantially improve the performance of persistent transactions. Our evaluation shows a substantial improvement in the both the latency and scalability of persistent transactions. 

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2. Twizzler: A Data-centric OS for Non-volatile Memory

   https://doi.org/10.1145/3454129  

   Bittman, Daniel; Alvaro, Peter; Mehra, Pankaj; Long, Darrell D.; Miller, Ethan L. (June 2021, ACM Transactions on Storage)

   Byte-addressable, non-volatile memory (NVM) presents an opportunity to rethink the entire system stack. We present Twizzler, an operating system redesign for this near-future. Twizzler removes the kernel from the I/O path, provides programs with memory-style access to persistent data using small (64 bit), object-relative cross-object pointers, and enables simple and efficient long-term sharing of data both between applications and between runs of an application. Twizzler provides a clean-slate programming model for persistent data, realizing the vision of Unix in a world of persistent RAM. We show that Twizzler is simpler, more extensible, and more secure than existing I/O models and implementations by building software for Twizzler and evaluating it on NVM DIMMs. Most persistent pointer operations in Twizzler impose less than 0.5 ns added latency. Twizzler operations are up to faster than Unix , and SQLite queries are up to faster than on PMDK. YCSB workloads ran 1.1– faster on Twizzler than on native and NVM-optimized SQLite backends. 

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3. AutoPersist: an easy-to-use Java NVM framework based on reachability

   https://doi.org/10.1145/3314221.3314608  

   Shull, Thomas; Huang, Jian; Torrellas, Josep (July 2019, Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation)

   Byte-addressable, non-volatile memory (NVM) is emerging as a revolutionary memory technology that provides persistency, near-DRAM performance, and scalable capacity. To facilitate its use, many NVM programming models have been proposed. However, most models require programmers to explicitly specify the data structures or objects that should reside in NVM. Such requirement increases the burden on programmers, complicates software development, and introduces opportunities for correctness and performance bugs. We believe that requiring programmers to identify the data structures that should reside in NVM is untenable. Instead, programmers should only be required to identify durable roots - the entry points to the persistent data structures at recovery time. The NVM programming framework should then automatically ensure that all the data structures reachable from these roots are in NVM, and stores to these data structures are persistently completed in an intuitive order. To this end, we present a new NVM programming framework, named AutoPersist, that only requires programmers to identify durable roots. AutoPersist then persists all the data structures that can be reached from the durable roots in an automated and transparent manner. We implement AutoPersist as a thread-safe extension to the Java language and perform experiments with a variety of applications running on Intel Optane DC persistent memory. We demonstrate that AutoPersist requires minimal code modifications, and significantly outperforms expert-marked Java NVM applications. 

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4. Reconciling Hardware Transactional Memory and Persistent Programming with Buffered Durability

   https://doi.org/10.1145/3694906.3743321  

   Du, Mingzhe; Su, Ziheng; Scott, Michael L (July 2025, ACM)

   Hardware Transactional Memory (HTM) simplifies concurrent programming and can accelerate multithreaded execution through lock elision. Non-Volatile Memory (NVM) combines the speed and byte addressability of DRAM with the durability of storage, enabling the construction of high-performance, persistent data structures. Unfortunately, the write-back instructions typically needed to ensure post-crash consistency in NVM cause HTM transactions to abort, precluding the straightforward combination of HTM and persistent data structures. The problem goes away on machines with persistent caches, but these require special battery-backed circuitry and are far from commonplace.To combine HTM and persistent data structures, we advocate for buffered durable linearizability (BDL), a relaxed correctness criterion that enables recovery to a "recent" consistent state in the wake of a crash, allowing writes-back to occur outside transactions.Significantly, BDL retains the persistence guarantees of storage systems—such as databases backed by disks or flash—that have relied on buffering for decades.The combination of HTM and buffered durability enables three separate usage scenarios. First, we add durability to an existing HTM-based structure (a van Emde Boas tree due to Khalaji et al.); second, we use HTM to simplify an existing persistent structure (a skiplist due to Wang et al.); third, we "back port" an HTM-based structure optimized for persistent caches (a hash table due to Zhang et al.) to work well on more conventional processors. The first two scenarios yield several-fold improvements in throughput; the third sees very little slowdown. 

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5. MSWasm: Soundly Enforcing Memory-Safe Execution of Unsafe Code

   https://doi.org/10.1145/3571208  

   Michael, Alexandra E.; Gollamudi, Anitha; Bosamiya, Jay; Johnson, Evan; Denlinger, Aidan; Disselkoen, Craig; Watt, Conrad; Parno, Bryan; Patrignani, Marco; Vassena, Marco; et al (January 2023, Proceedings of the ACM on Programming Languages)

   Most programs compiled to WebAssembly (Wasm) today are written in unsafe languages like C and C++. Unfortunately, memory-unsafe C code remains unsafe when compiled to Wasm—and attackers can exploit buffer overflows and use-after-frees in Wasm almost as easily as they can on native platforms. Memory- Safe WebAssembly (MSWasm) proposes to extend Wasm with language-level memory-safety abstractions to precisely address this problem. In this paper, we build on the original MSWasm position paper to realize this vision. We give a precise and formal semantics of MSWasm, and prove that well-typed MSWasm programs are, by construction, robustly memory safe. To this end, we develop a novel, language-independent memory-safety property based on colored memory locations and pointers. This property also lets us reason about the security guarantees of a formal C-to-MSWasm compiler—and prove that it always produces memory-safe programs (and preserves the semantics of safe programs). We use these formal results to then guide several implementations: Two compilers of MSWasm to native code, and a C-to-MSWasm compiler (that extends Clang). Our MSWasm compilers support different enforcement mechanisms, allowing developers to make security-performance trade-offs according to their needs. Our evaluation shows that on the PolyBenchC suite, the overhead of enforcing memory safety in software ranges from 22% (enforcing spatial safety alone) to 198% (enforcing full memory safety), and 51.7% when using hardware memory capabilities for spatial safety and pointer integrity. More importantly, MSWasm’s design makes it easy to swap between enforcement mechanisms; as fast (especially hardware-based) enforcement techniques become available, MSWasm will be able to take advantage of these advances almost for free. 

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