Bibliometrics

SECTION: Special Issue on FPGAs in Data Centers, Part 2

research-article
AIgean: An Open Framework for Deploying Machine Learning on Heterogeneous Clusters
September 2022, Article No.: 23, pp 1–32https://doi.org/10.1145/3482854

 AIgean, pronounced like the sea, is an open framework to build and deploy machine learning (ML) algorithms on a heterogeneous cluster of devices (CPUs and FPGAs). We leverage two open source projects: Galapagos, for multi-FPGA deployment, and hls4ml, for ...

research-article
Open Access
A Unified FPGA Virtualization Framework for General-Purpose Deep Neural Networks in the Cloud
September 2022, Article No.: 24, pp 1–31https://doi.org/10.1145/3480170

INFerence-as-a-Service (INFaaS) has become a primary workload in the cloud. However, existing FPGA-based Deep Neural Network (DNN) accelerators are mainly optimized for the fastest speed of a single task, while the multi-tenancy of INFaaS has not been ...

research-article
Open Access
Scalable Phylogeny Reconstruction with Disaggregated Near-memory Processing
September 2022, Article No.: 25, pp 1–32https://doi.org/10.1145/3484983

Disaggregated computer architectures eliminate resource fragmentation in next-generation datacenters by enabling virtual machines to employ resources such as CPUs, memory, and accelerators that are physically located on different servers. While this paves ...

SECTION: Regular Papers

research-article
A Real-Time Deep Learning OFDM Receiver
September 2022, Article No.: 26, pp 1–25https://doi.org/10.1145/3494049

Machine learning in the physical layer of communication systems holds the potential to improve performance and simplify design methodology. Many algorithms have been proposed; however, the model complexity is often unfeasible for real-time deployment. The ...

research-article
Design of Distributed Reconfigurable Robotics Systems with ReconROS
September 2022, Article No.: 27, pp 1–20https://doi.org/10.1145/3494571

Robotics applications process large amounts of data in real time and require compute platforms that provide high performance and energy efficiency. FPGAs are well suited for many of these applications, but there is a reluctance in the robotics community ...

research-article
Approaches for FPGA Design Assurance
September 2022, Article No.: 28, pp 1–29https://doi.org/10.1145/3491233

Field-Programmable Gate Arrays (FPGAs) are widely used for custom hardware implementations, including in many security-sensitive industries, such as defense, communications, transportation, medical, and more. Compiling source hardware descriptions to FPGA ...

research-article
Approximate Constant-Coefficient Multiplication Using Hybrid Binary-Unary Computing for FPGAs
September 2022, Article No.: 29, pp 1–25https://doi.org/10.1145/3494570

Multipliers are used in virtually all Digital Signal Processing (DSP) applications such as image and video processing. Multiplier efficiency has a direct impact on the overall performance of such applications, especially when real-time processing is ...

research-article
Open Access
Improving Loop Parallelization by a Combination of Static and Dynamic Analyses in HLS
September 2022, Article No.: 31, pp 1–31https://doi.org/10.1145/3501801

High-level synthesis (HLS) can be used to create hardware accelerators for compute-intense software parts such as loop structures. Usually, this process requires significant amount of user interaction to steer kernel selection and optimizations. This can ...

research-article
Quick-Div: Rethinking Integer Divider Design for FPGA-based Soft-processors
September 2022, Article No.: 32, pp 1–27https://doi.org/10.1145/3502492

In today’s FPGA-based soft-processors, one of the slowest instructions is integer division. Compared to the low single-digit latency of other arithmetic operations, the fixed 32-cycle latency of radix-2 division is substantially longer. Given that today’s ...

research-article
The Future of FPGA Acceleration in Datacenters and the Cloud
September 2022, Article No.: 34, pp 1–42https://doi.org/10.1145/3506713

In this article, we survey existing academic and commercial efforts to provide Field-Programmable Gate Array (FPGA) acceleration in datacenters and the cloud. The goal is a critical review of existing systems and a discussion of their evolution from ...

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