Concept

In-memory processing

Related publications (32)

The Mondrian Data Engine

Babak Falsafi, Boris Robert Grot, Alexandros Daglis, Javier Picorel Obando, Mario Paulo Drumond Lages De Oliveira, Dionysios Pnevmatikatos, Dmitrii Ustiugov, Nooshin Sadat Mirzadeh

The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

2017

Toward timely, predictable and cost-effective data analytics

Renata Borovica-Gajic

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

EPFL2016

Sort vs. Hash Join Revisited for Near-Memory Execution

Babak Falsafi, Boris Robert Grot, Yusuf Onur Koçberber, Nooshin Sadat Mirzadeh

Data movement between memory and CPU is a well-known energy bottleneck for analytics. Near-Memory Processing (NMP) is a promising approach for eliminating this bottleneck by shifting the bulk of the computation toward memory arrays in emerging stacked DRAM ...

2015

Sort vs. Hash Join Revisited for Near-Memory Execution

Babak Falsafi, Boris Robert Grot, Yusuf Onur Koçberber, Nooshin Sadat Mirzadeh

2015

Scaling the Memory Power Wall with DRAM-Aware Data Management

Anastasia Ailamaki, Raja Appuswamy, Matthaios Alexandros Olma

Improving the energy efficiency of database systems has emerged as an important topic of research over the past few years. While significant attention has been paid to optimizing the power consumption of tradition disk-based databases, little attention has ...

ACM2015

Runtime Prediction for Scale-Out Data Analytics

Adrian Daniel Popescu

Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...

EPFL2015

Query Optimization in Oracle 12c Database In-Memory

Ramachandra Satyanarayana Valluri

Traditional on disk row major tables have been the dominant storage mechanism in relational databases for decades. Over the last decade, however, with explosive growth in data volume and demand for faster analytics, has come the recognition that a differen ...

2015

Adaptive Query Processing on RAW Data

Anastasia Ailamaki, Miguel Sérgio De Oliveira Branco, Manolis Karpathiotakis, Ioannis Alagiannis

Database systems deliver impressive performance for large classes of workloads as the result of decades of research into optimizing database engines. High performance, however, is achieved at the cost of versatility. In particular, database systems only op ...

2014

Scalable and Adaptive Online Joins

Christoph Koch, Aleksandar Vitorovic, Abdallah Alaaeldin Abdelaziz Elguindy

Scalable join processing in a parallel shared-nothing environment requires a partitioning policy that evenly distributes the processing load while minimizing the size of state maintained and number of messages communicated. Previous research proposes stati ...

VLDB2014

Efficient Indexing and Query Processing of Model-View Sensor Data in the Cloud

Karl Aberer, Tian Guo

As the number of sensors that pervade our lives increases (e.g., environmental sensors, phone sensors, etc.), the eﬃcient management of massive amount of sensor data is becoming increasingly important. The inﬁnite nature of sensor data poses a serious chal ...

2014

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