FADE: A Programmable Filtering Accelerator for Instruction-Grain Monitoring

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

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 ...

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 ...

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 ...

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 ...

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

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 ...

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been developed and ha ...

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

Timely insights lead to business growth and scientific breakthroughs but require analytical engines that cope with the ever-increasing data processing needs. Analytical engines relied on rapid CPU improvements, yet the end of Dennard scaling stopped the fr ...

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

Enumerating simple cycles has important applications in computational biology, network science, and financial crime analysis. In this work, we focus on parallelising the state-of-the-art simple cycle enumeration algorithms by Johnson and Read-Tarjan along ...

FPGAs are proving useful and attractive for many applications, thanks to their hardware reconfigurability, low power, and high-degree of parallelism. As a result, modern embedded systems are often based on systems-on-chip (SoCs), where CPUs and FPGAs share ...

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 ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

This paper presents an ultra-high-throughput decoder architecture for NB-LDPC codes based on the Hybrid Extended Min-Sum algorithm. We introduce a new processing block that updates a check node and its associated variable nodes in a fully pipelined way, th ...

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

FADE: A Programmable Filtering Accelerator for Instruction-Grain Monitoring

Chat with Graph Search

EdgeAI-Aware Design of In-Memory Computing Architectures

Rebooting Virtual Memory with Midgard

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

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

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

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

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Impact of Video Processing Operations in Deepfake Detection

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Efficient Analytical Query Processing on CPU-GPU Hardware Platforms

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Scalable Fine-Grained Parallel Cycle Enumeration Algorithms

FPGA-to-CPU Undervolting Attacks

Boosting Efficiency of External Pipelines by Blurring Application Boundaries

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

Ultra-High-Throughput EMS NB-LDPC Decoder with Full-Parallel Node Processing

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

From C/C plus plus Code to High-Performance Dataflow Circuits

Micro-architectural Analysis of Database Workloads