Universally Scalable Concurrent Data Structures

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Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

In this paper, we propose an analytical stochastic dynamic programming (SDP) algorithm to address the optimal management problem of price-maker community energy storage. As a price-maker, energy storage smooths price differences, thus decreasing energy arb ...

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

The popular isolation level multiversion Read Committed (RC) exchanges some of the strong guarantees of serializability for increased transaction throughput. Nevertheless, transaction workloads can sometimes be executed under RC while still guaranteeing se ...

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Userspace library file systems (LibFSes) promise to unleash the performance potential of non-volatile memory (NVM) by directly accessing it and enabling unprivileged applications to customize their LibFSes to their workloads. Unfortunately, such benefits p ...

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

Key-Value Stores (KVS) are foundational infrastructure components for online services. Due to their latency-critical nature, today’s best-performing KVS contain a plethora of full-stack optimizations commonly targeting read-mostly, popularity-skewed worklo ...

Universally Scalable Concurrent Data Structures

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EdgeAI-Aware Design of In-Memory Computing Architectures

Secure Interface Design Leveraging Hardware/Software Support

Oligolithic Cross-task Optimizations across Isolated Workloads

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Highly Parallel RTL Simulation

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming

Automated Formal Verification of Software Network Functions

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

Rebooting Virtual Memory with Midgard

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

When is it safe to run a transactional workload under Read Committed?

HPCache: memory-efficient OLAP through proportional caching revisited

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

Chaosity: Understanding Contemporary NUMA-architectures

Enabling High-Performance and Secure Userspace NVM File Systems with the Trio Architecture

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Cooperative Concurrency Control for Write-Intensive Key-Value Workloads