Výsledky vyhľadávania - Computer systems organization Architectures Other architectures Reconfigurable computing
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DRISA: a DRAM-based Reconfigurable In-Situ Accelerator
ISBN: 1450349528, 9781450349529ISSN: 2379-3155Vydavateľské údaje: New York, NY, USA ACM 14.10.2017Vydané v MICRO-50 : the 50th annual IEEE/ACM International Symposium on Microarchitecture : proceedings : October 14-18, 2017, Cambridge, MA (14.10.2017)“… To address the challenge, we propose DRISA, a DRAM-based Reconfigurable In-Situ Accelerator architecture, to provide both powerful computing capability and large memory capacity/bandwidth…”
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Caffeine: Towards uniformed representation and acceleration for deep convolutional neural networks
ISSN: 1558-2434Vydavateľské údaje: ACM 01.11.2016Vydané v Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design (01.11.2016)“… Second, we design Caffeine with the goal to maximize the underlying FPGA computing and bandwidth…”
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Stream-dataflow acceleration
Vydavateľské údaje: ACM 01.06.2017Vydané v 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA) (01.06.2017)“…) are insufficient, as evidenced by the order-of-magnitude improvements and industry adoption of application and domain-specific accelerators in important areas like machine learning, computer vision and big data…”
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SODA: Stencil with Optimized Dataflow Architecture
ISSN: 1558-2434Vydavateľské údaje: ACM 01.11.2018Vydané v 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (01.11.2018)“… In this paper we present SODA, an automated framework for implementing Stencil algorithms with Optimized Dataflow Architecture on FPGAs…”
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Maximizing CNN accelerator efficiency through resource partitioning
Vydavateľské údaje: ACM 01.06.2017Vydané v 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA) (01.06.2017)“…Convolutional neural networks (CNNs) are revolutionizing machine learning, but they present significant computational challenges. Recently, many FPGA-based…”
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Qubit Mapping for Reconfigurable Atom Arrays
ISSN: 1558-2434Vydavateľské údaje: ACM 29.10.2022Vydané v 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD) (29.10.2022)“…Because of the largest number of qubits available, and the massive parallel execution of entangling two-qubit gates, atom arrays is a promising platform for quantum computing…”
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FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching
Vydavateľské údaje: IEEE 29.06.2024Vydané v 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) (29.06.2024)“…The inference of ML models composed of diverse structures, types, and sizes boils down to the execution of different dataflows (i.e. different tiling,…”
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Understanding and optimizing asynchronous low-precision stochastic gradient descent
Vydavateľské údaje: ACM 01.06.2017Vydané v 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA) (01.06.2017)“…Stochastic gradient descent (SGD) is one of the most popular numerical algorithms used in machine learning and other domains. Since this is likely to continue…”
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MECLA: Memory-Compute-Efficient LLM Accelerator with Scaling Sub-matrix Partition
Vydavateľské údaje: IEEE 29.06.2024Vydané v 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) (29.06.2024)“…Large language models (LLMs) have been showing surprising performance in processing language tasks, bringing a new prevalence to deploy LLM from cloud to edge…”
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TGPA: Tile-Grained Pipeline Architecture for Low Latency CNN Inference
ISSN: 1558-2434Vydavateľské údaje: ACM 01.11.2018Vydané v 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (01.11.2018)“…FPGAs are more and more widely used as reconfigurable hardware accelerators for applications leveraging convolutional neural networks (CNNs) in recent years…”
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Map-and-Conquer: Energy-Efficient Mapping of Dynamic Neural Nets onto Heterogeneous MPSoCs
Vydavateľské údaje: IEEE 09.07.2023Vydané v 2023 60th ACM/IEEE Design Automation Conference (DAC) (09.07.2023)“… To date, the mapping strategies of neural networks (NNs) onto such systems are yet to exploit the full potential of processing parallelism, made possible through both the intrinsic NNs' structure and underlying hardware composition…”
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HAL: Hardware-assisted Load Balancing for Energy-efficient SNIC-Host Cooperative Computing
Vydavateľské údaje: IEEE 29.06.2024Vydané v 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) (29.06.2024)“… With such a processor, the SNIC has promised to notably improve the system-wide energy efficiency of datacenter servers…”
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MambaOPU: An FPGA Overlay Processor for State-space-duality-based Mamba Models
Vydavateľské údaje: IEEE 22.06.2025Vydané v 2025 62nd ACM/IEEE Design Automation Conference (DAC) (22.06.2025)“…State-space models (SSMs), such as Mamba, have emerged as a promising alternative to Transformers. However, the recently developed Mamba2, based on state space…”
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CoSPARSE: A Software and Hardware Reconfigurable SpMV Framework for Graph Analytics
Vydavateľské údaje: IEEE 05.12.2021Vydané v 2021 58th ACM/IEEE Design Automation Conference (DAC) (05.12.2021)“… reconfiguration as a synergistic solution to accelerate SpMV-based graph analytics algorithms. Building on previously proposed general-purpose reconfigurable hardware…”
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Heterogeneous Reconfigurable Accelerators: Trends and Perspectives
Vydavateľské údaje: IEEE 09.07.2023Vydané v 2023 60th ACM/IEEE Design Automation Conference (DAC) (09.07.2023)“…Heterogeneity and reconfigurability have both been adopted by accelerators to improve their flexibility and efficiency for a wide variety of applications, from cloud computing to embedded systems…”
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Hardware-Aware Machine Learning: Modeling and Optimization
ISSN: 1558-2434Vydavateľské údaje: ACM 01.11.2018Vydané v 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (01.11.2018)“…), have made DL models a key component in almost every modern computing system. The increased popularity of DL applications deployed on a wide-spectrum of platforms…”
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MASR: A Modular Accelerator for Sparse RNNs
ISSN: 2641-7936Vydavateľské údaje: IEEE 01.09.2019Vydané v Proceedings / International Conference on Parallel Architectures and Compilation Techniques (01.09.2019)“… In this paper we present MASR, a principled and modular architecture that accelerates bidirectional RNNs for on-chip ASR…”
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RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU
Vydavateľské údaje: IEEE 05.12.2021Vydané v 2021 58th ACM/IEEE Design Automation Conference (DAC) (05.12.2021)“…As AI-based applications become pervasive, CPU vendors are starting to incorporate matrix engines within the datapath to boost efficiency. Systolic arrays have…”
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RADiT: Redundancy-Aware Diffusion Transformer Acceleration Leveraging Timestep Similarity
Vydavateľské údaje: IEEE 22.06.2025Vydané v 2025 62nd ACM/IEEE Design Automation Conference (DAC) (22.06.2025)“…Diffusion Transformers (DiTs) have demonstrated unprecedented performance across various generative tasks including image and video generation. However, a…”
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Buffer Prospector: Discovering and Exploiting Untapped Buffer Resources in Many-Core DNN Accelerators
Vydavateľské údaje: IEEE 22.06.2025Vydané v 2025 62nd ACM/IEEE Design Automation Conference (DAC) (22.06.2025)“…In large-scale DNN inference accelerators, the many-core architecture has emerged as a predominant design, with layer-pipeline (LP…”
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