Adaptive Cache Mode Selection for Queries over Raw Data

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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 ...

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 ...

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 ...

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 ...

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

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 ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

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 ...

Numerical simulations have become an indispensable tool in astrophysics and cosmology. The constant need for higher accuracy, higher resolutions, and models of ever-increasing sophistication and complexity drives the development of modern tools which targe ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

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 ...

Code-reuse attacks are dangerous threats that attracted the attention of the security community for years. These attacks aim at corrupting important control-flow transfers for taking control of a process without injecting code. Nowadays, the combinations o ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

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

As a unified data repository, data lake plays a vital role in enterprise data management and analysis. It composes the raw files into tables that are processed in-situ by various computation engines and applications. Therefore, the read performance of the ...

Utilization of edge devices has exploded in the last decade, with such use cases as wearable devices, autonomous driving, and smart homes. As their ubiquity grows, so do expectations of their capabilities. Simultaneously, their formfactor and use cases lim ...

High-performance branch target buffers (BTBs) and the L1I cache are key to high-performance front-end. Modern branch predictors are highly accurate, but with an increase in code footprint in modern-day server workloads, BTB and L1I misses are still frequen ...

Applications such as large-scale sparse linear algebra and graph analytics are challenging to accelerate on FPGAs due to the short irregular memory accesses, resulting in low cache hit rates. Nonblocking caches reduce the bandwidth required by misses by re ...

With the increasing dominance of SSDs for local storage, today's network mounted virtual disks can no longer offer competitive performance. We propose a Log-Structured Virtual Disk (LSVD) that couples log-structured approaches at both the cache and storage ...

Adaptive Cache Mode Selection for Queries over Raw Data

Chattez avec Graph Search

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

EdgeAI-Aware Design of In-Memory Computing Architectures

HPCache: memory-efficient OLAP through proportional caching revisited

Rebooting Virtual Memory with Midgard

uKharon: A Membership Service for Microsecond Applications

Fast correlation function calculator A high-performance pair-counting toolkit

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

Caching and Neutrality

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

GEAR-RT: Towards Exa-Scale Moment Based Radiative Transfer For Cosmological Simulations Using Task-Based Parallelism And Dynamic Sub-Cycling with SWIFT

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

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

WarpAttack: Bypassing CFI through Compiler-Introduced Double-Fetches

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

HPCache: Memory-Efficient OLAP Through Proportional Caching

Columnar Storage Optimization and Caching for Data Lakes

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

Micro BTB: A High Performance and Storage Efficient Last-Level Branch Target Buffer for Servers

Request, Coalesce, Serve, and Forget: Miss-Optimized Memory Systems for Bandwidth-Bound Cache-Unfriendly Applications on FPGAs

Beating the I/O Bottleneck: A Case for Log-Structured Virtual Disks