Publications by Anastasia Ailamaki

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To sustain the input rate of high-throughput streams, modern stream processing systems rely on parallel execution. However, skewed data yield imbalanced load assignments and create stragglers that hinder scalability. Deciding on a static partitioning for a ...

Power and cooling costs are some of the highest costs in data centers today, which make improvement in energy efficiency crucial. Energy efficiency is also a major design point for chips that power whole ranges of computing devices. One important goal in t ...

Modern Hybrid Transactional/Analytical Processing (HTAP) systems use an integrated data processing engine that performs analytics on fresh data, which are ingested from a transactional engine. HTAP systems typically consider data freshness at design time, ...

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management nece ...

Hardware trends oblige software to overcome three major challenges against systems scalability: (1) taking advantage of the implicit/vertical parallelism within a core that is enabled through the aggressive micro-architectural features, (2) exploiting the ...

Even though main memory is becoming large enough to fit most OLTP databases, it may not always be the best option. OLTP workloads typically exhibit skewed access patterns where some records are hot (frequently accessed) but many records are cold (infrequen ...

Store misses cause significant delays in shared-memory multiprocessors because of limited store buffering and ordering constraints required for proper synchronization. Today, programmers must choose from a spectrum of memory consistency models that reduce ...

Systems and method for a task scheduler with dynamic adjustment of concurrency levels and task granularity are disclosed for improved execution of highly concurrent analytical and transactional systems. The task scheduler can avoid both over commitment and ...

Modern application development addresses increasingly specialized problems using domain-specific utilities, such as Optical Code Recognition and standalone statistical tools. The diversity of tooling, combined with the ever-growing volume of data, requires ...

Transaction processing workloads provide ample request level concurrency which highly parallel architectures can exploit. However, the resulting heavy utilization of core database services also causes resource contention within the database engine itself a ...

While hardware technology has undergone major advancements over the past decade, transaction processing systems have remained largely unchanged. The number of cores on a chip grows exponentially, following Moore's Law, allowing for an ever-increasing numbe ...

A major component of many cloud services is query processing on data stored in the underlying cloud cluster. The traditional techniques for query processing on a cluster are those offered by parallel DBMS. These techniques however, cannot guarantee high pe ...

Introduced in 2007, TPC-E is the most recently standardized OLTP benchmark by TPC. Even though TPC-E has already been around for six years, it has not gained the popularity of its predecessor TPC-C: all the published results for TPC-E use a single database ...

In chip multiprocessors (CMPs), limiting the number of offchip cache misses is crucial for good performance. Many multithreaded programs provide opportunities for constructive cache sharing, in which concurrently scheduled threads share a largely overlappi ...

Prior research shows that database system performance is dominated by off-chip data stalls, resulting in a concerted effort to bring data into on-chip caches. At the same time, high levels of integration have enabled the advent of chip multiprocessors and ...

GPUs are becoming increasingly popular in large scale data center installations due to their strong, embarrassingly parallel, processing capabilities. Data management systems are riding the wave by using GPUs to accelerate query execution, mainly for analy ...

Data cleaning is a time-consuming process that depends on the data analysis that users perform. Existing solutions treat data cleaning as a separate offline process that takes place before analysis begins. Applying data cleaning before analysis assumes a p ...

As data collections become larger and larger, users are faced with increasing bottlenecks in their data analysis. More data means more time to prepare and to load the data into the database before executing the desired queries. Many applications already av ...

Task scheduling typically employs a worker thread per hardware context to process a dynamically changing set of tasks. It is an appealing solution to exploit modern multi-core processors, as it eases parallelization and avoids unnecessary context switches ...

Designing scalable transaction processing systems on modern hardware has been a challenge for almost a decade. Hardware trends oblige software to overcome three major challenges against systems scalability: (1) Exploiting the abundant thread-level parallel ...

Anastasia Ailamaki

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Dalton: Learned Partitioning for Distributed Data Streams

Dynamic Fine-Grained Scheduling for Energy-Efficient Main-Memory Queries

Adaptive HTAP through Elastic Resource Scheduling

Optimal service pricing for a cloud cache

How to Stop Under-Utilization and Love Multicores

Enabling efficient OS paging for main-memory OLTP databases

Mechanisms for store-wait-free multiprocessors

Task scheduling for highly concurrent analytical and transaction workloads

Boosting Efficiency of External Pipelines by Blurring Application Boundaries

Improving OLTP Scalability Using Speculative Lock Inheritance

Data-Oriented Transaction Execution

Adaptive query execution for data management in the cloud

From A to E: Analyzing TPC’s OLTP Benchmarks -- The obsolete, the ubiquitous, the unexplored

Scheduling threads for constructive cache sharing on CMPs

An Analysis of Database System Performance on Chip Multiprocessors

GPU-accelerated data management under the test of time

Query-driven Repair of Functional Dependency Violations

NoDB: Efficient Query Execution on Raw Data Files

Task Scheduling for Highly Concurrent Analytical and Transactional Main-Memory Workloads

How to Stop Under-Utilization and Love Multicores