arXiv subjects

Tomoharu Ugawa

Publications and source records attributed to Tomoharu Ugawa.

4 recordsLinked to original sources

arXiv2026

Query Density-Driven Partitioning for Spatiotemporal Load Balancing on Processing-in-Memory Systems

Processing-in-Memory (PIM) systems, which consist of many processors with small local memory, have recently emerged as commercial products and attracted much attention as a means of overcoming the memory wall, particularly in the context of in-memory database technology. The state-of-the-art PIM-oriented index PIM-tree has been demonstrated to achieve asymptotically good spatiotemporal load balancing---query loads and data sizes are balanced among processors---for skewed queries, by trading spatial locality. Unfortunately, such a sacrifice of spatial locality hinders the PIM-oriented processing of range-aggregate queries. To achieve both spatiotemporal load balancing and efficiently executing range-aggregate queries on PIM systems, we develop a query density-driven key-range partitioning scheme. It balances query density among PIM processors, allowing us to strike a balance between query load and data size via a parameter. We then develop B${}^\text{+}$-Forest, a PIM-oriented B${}^\text{+}$-tree variant based on our partitioning scheme. Experimental results demonstrated that it exhibits higher skew resistance than a B${}^\text{+}$-tree based on space-constrained, query-load-balanced, density-unaware partitioning, and performance comparable to PIM-tree in point-get queries, as well as efficient support for range-aggregate queries.

cs.DB↗

arXiv2026

Pitfalls in VM Implementation on CHERI: Lessons from Porting CRuby

CHERI (Capability Hardware Enhanced RISC Instructions) is a novel hardware designed to address memory safety issues. By replacing traditional pointers with hardware capabilities, it enhances security in modern software systems. A Virtual Machine (VM) is one such system that can benefit from CHERI's protection, as it may contain latent memory vulnerabilities. However, developing and porting VMs to CHERI is a non-trivial task. There are many subtle pitfalls from the assumptions on the undefined behaviors of the C language made based on conventional architectures. Those assumptions conflict with CHERI's stricter memory safety model, causing unexpected failures. Although several prior works have discussed the process of porting VMs, they focus on the overall porting process instead of the pitfalls for VM implementation on CHERI. The guide for programming in CHERI exists, but it is for general programming, not addressing VM-specific issues. We have ported CRuby to CHERI as a case study and surveyed previous works on porting VMs to CHERI. We categorized and discussed the issues found based on their causes. In this paper, we illustrate the VM-specific pitfalls for each category. Most of the pitfalls arise from the undefined behaviors in the C language; in particular, implementation techniques and idioms of VMs often assume behaviors of traditional architectures that are invalid on CHERI. We also discuss workarounds for them and the impacts of those workarounds. We verified the validity of the workarounds by applying them to our CRuby port and by surveying the codebases of prior case studies. This work contributes to the body of knowledge on developing and porting VMs to CHERI and will help guide efforts toward constructing safer VMs.

cs.PL↗

arXiv2024

Collective Allocator Abstraction to Control Object Spatial Locality in C++

Disaggregated memory is promising for improving memory utilization in computer clusters in which memory demands significantly vary across computer nodes under utilization. It allows applications with high memory demands to use memory in other computer nodes. However, disaggregated memory is not easy to use for implementing data structures in C++ because the C++ standard does not provide an adequate abstraction to use it efficiently in a high-level, modular manner. Because accessing remote memory involves high latency, disaggregated memory is often used as a far-memory system, which forms a kind of swap memory where part of local memory is used as a cache area, while the remaining memory is not subject to swapping. To pursue performance, programmers have to be aware of this nonuniform memory view and place data appropriately to minimize swapping. In this work, we model the address space of memory-disaggregated systems as the far-memory model, present the collective allocator abstraction, which enables us to specify object placement aware of memory address subspaces, and apply it to programming aware of the far-memory model. The far-memory model provides a view of the nonuniform memory space while hiding the details. In the model, the virtual address space is divided into two subspaces; one is subject to swapping and the other is not. The swapping subspace is further divided into even-sized pages, which are units of swapping. The collective allocator abstraction forms an allocator as a collection of sub-allocators, each of which owns a distinct subspace, where every allocation is done via sub-allocators. It enables us to control object placement at allocation time by selecting an appropriate sub-allocator according to different criteria, such as subspace characteristics and object collocation. It greatly facilitates implementing container data structures aware of the far-memory model. We develop an allocator based on the collective allocator abstraction by extending the C++ standard allocator for container data structures on the far-memory model and experimentally demonstrate that it facilitates implementing containers equipped with object placement strategies aware of spatial locality under the far-memory model in a high-level, modular manner. More specifically, we have successfully implemented B-trees and skip lists with the combined use of two placement strategies. The modifications therein for the original implementations are fairly modest: addition is mostly due to specifying object placement; deletion and modification are at most 1.2 % and 3.2 % of lines of the original code, respectively. We have experimentally confirmed that the modified implementations successfully have data layouts suppressing swapping. We forecast that the collective allocator abstraction would be a key to high-level integration with different memory hardware technologies because it straightforwardly accommodates new interfaces for subspaces.

cs.PL↗

arXiv2016

Reducing State Explosion for Software Model Checking with Relaxed Memory Consistency Models

Software model checking suffers from the so-called state explosion problem, and relaxed memory consistency models even worsen this situation. What is worse, parameterizing model checking by memory consistency models, that is, to make the model checker as flexible as we can supply definitions of memory consistency models as an input, intensifies state explosion. This paper explores specific reasons for state explosion in model checking with multiple memory consistency models, provides some optimizations intended to mitigate the problem, and applies them to McSPIN, a model checker for memory consistency models that we are developing. The effects of the optimizations and the usefulness of McSPIN are demonstrated experimentally by verifying copying protocols of concurrent copying garbage collection algorithms. To the best of our knowledge, this is the first model checking of the concurrent copying protocols under relaxed memory consistency models.

cs.SE↗