Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384705423> ?p ?o ?g. }
Showing items 1 to 99 of
99
with 100 items per page.
- W4384705423 abstract "Register Transfer Level (RTL) simulation and verification of Digital Circuits are extremely important and costly tasks in the Integrated Circuits industry. While some simulators have incorporated the exploitation of parallelism in the structure of Digital Circuits to run on multi-core CPUs, the maximum throughput they achieve quickly reaches a plateau, as described by Amdahl’s Law. Recent research from Nvidia has obtained much higher throughput in simulations using GPUs, highlighting the potential of these devices for Digital Circuit simulation. However, they were required to incorporate sophisticated algorithms to support GPU simulation. In addition, the unbalanced structure of real-life Digital Circuits provides difficulties for processing on multi-threaded devices. In this paper, we present a Digital Circuit compiler that utilizes Neural Networks to exploit the various parallelisms in RTL simulation, making use of PyTorch, a widely-used Neural Network framework that facilitate their simulation on GPUs. By using properties of Boolean Functions, we developed a novel algorithm that converts any Digital Circuit into a Neural Network, and optimization techniques that help in pushing the thread computational capability to the limit. The results show three orders of magnitude higher throughput than Verilator RTL simulator, an improvement of one order of magnitude compared to the state-of-the-art GPU techniques from Nvidia. We believe that the use of Neural Networks not only provides a significant improvement in simulation and verification tasks in the Integrated Circuits industry, but also opens a line of research for simulators at the logic and physical gate level." @default.
- W4384705423 created "2023-07-20" @default.
- W4384705423 creator A5038789440 @default.
- W4384705423 creator A5055968320 @default.
- W4384705423 creator A5071712019 @default.
- W4384705423 creator A5075992947 @default.
- W4384705423 creator A5089033353 @default.
- W4384705423 date "2023-05-01" @default.
- W4384705423 modified "2023-10-18" @default.
- W4384705423 title "Neural Network Compiler for Parallel High-Throughput Simulation of Digital Circuits" @default.
- W4384705423 cites W1528837436 @default.
- W4384705423 cites W1979855816 @default.
- W4384705423 cites W2044033049 @default.
- W4384705423 cites W2056748176 @default.
- W4384705423 cites W2064141391 @default.
- W4384705423 cites W2095266728 @default.
- W4384705423 cites W2102591716 @default.
- W4384705423 cites W2105715355 @default.
- W4384705423 cites W2130402533 @default.
- W4384705423 cites W2277653173 @default.
- W4384705423 cites W2761973445 @default.
- W4384705423 cites W3014939941 @default.
- W4384705423 cites W3071517735 @default.
- W4384705423 cites W3092265192 @default.
- W4384705423 cites W3102754027 @default.
- W4384705423 cites W3105432754 @default.
- W4384705423 cites W3114262462 @default.
- W4384705423 cites W3130660608 @default.
- W4384705423 cites W3146200412 @default.
- W4384705423 cites W41330591 @default.
- W4384705423 cites W4237630008 @default.
- W4384705423 cites W4285194474 @default.
- W4384705423 cites W4312253630 @default.
- W4384705423 cites W4320067872 @default.
- W4384705423 doi "https://doi.org/10.1109/ipdps54959.2023.00067" @default.
- W4384705423 hasPublicationYear "2023" @default.
- W4384705423 type Work @default.
- W4384705423 citedByCount "0" @default.
- W4384705423 crossrefType "proceedings-article" @default.
- W4384705423 hasAuthorship W4384705423A5038789440 @default.
- W4384705423 hasAuthorship W4384705423A5055968320 @default.
- W4384705423 hasAuthorship W4384705423A5071712019 @default.
- W4384705423 hasAuthorship W4384705423A5075992947 @default.
- W4384705423 hasAuthorship W4384705423A5089033353 @default.
- W4384705423 hasConcept C113775141 @default.
- W4384705423 hasConcept C11413529 @default.
- W4384705423 hasConcept C118524514 @default.
- W4384705423 hasConcept C119599485 @default.
- W4384705423 hasConcept C127413603 @default.
- W4384705423 hasConcept C131017901 @default.
- W4384705423 hasConcept C134146338 @default.
- W4384705423 hasConcept C154945302 @default.
- W4384705423 hasConcept C157764524 @default.
- W4384705423 hasConcept C169590947 @default.
- W4384705423 hasConcept C173608175 @default.
- W4384705423 hasConcept C199360897 @default.
- W4384705423 hasConcept C2778119891 @default.
- W4384705423 hasConcept C41008148 @default.
- W4384705423 hasConcept C50644808 @default.
- W4384705423 hasConcept C555944384 @default.
- W4384705423 hasConcept C64859876 @default.
- W4384705423 hasConcept C76155785 @default.
- W4384705423 hasConcept C81843906 @default.
- W4384705423 hasConceptScore W4384705423C113775141 @default.
- W4384705423 hasConceptScore W4384705423C11413529 @default.
- W4384705423 hasConceptScore W4384705423C118524514 @default.
- W4384705423 hasConceptScore W4384705423C119599485 @default.
- W4384705423 hasConceptScore W4384705423C127413603 @default.
- W4384705423 hasConceptScore W4384705423C131017901 @default.
- W4384705423 hasConceptScore W4384705423C134146338 @default.
- W4384705423 hasConceptScore W4384705423C154945302 @default.
- W4384705423 hasConceptScore W4384705423C157764524 @default.
- W4384705423 hasConceptScore W4384705423C169590947 @default.
- W4384705423 hasConceptScore W4384705423C173608175 @default.
- W4384705423 hasConceptScore W4384705423C199360897 @default.
- W4384705423 hasConceptScore W4384705423C2778119891 @default.
- W4384705423 hasConceptScore W4384705423C41008148 @default.
- W4384705423 hasConceptScore W4384705423C50644808 @default.
- W4384705423 hasConceptScore W4384705423C555944384 @default.
- W4384705423 hasConceptScore W4384705423C64859876 @default.
- W4384705423 hasConceptScore W4384705423C76155785 @default.
- W4384705423 hasConceptScore W4384705423C81843906 @default.
- W4384705423 hasFunder F4320332180 @default.
- W4384705423 hasLocation W43847054231 @default.
- W4384705423 hasOpenAccess W4384705423 @default.
- W4384705423 hasPrimaryLocation W43847054231 @default.
- W4384705423 hasRelatedWork W1484077763 @default.
- W4384705423 hasRelatedWork W184060744 @default.
- W4384705423 hasRelatedWork W2017579069 @default.
- W4384705423 hasRelatedWork W2051378172 @default.
- W4384705423 hasRelatedWork W2522457226 @default.
- W4384705423 hasRelatedWork W2908634196 @default.
- W4384705423 hasRelatedWork W2911878640 @default.
- W4384705423 hasRelatedWork W3013976982 @default.
- W4384705423 hasRelatedWork W3141551763 @default.
- W4384705423 hasRelatedWork W4318224782 @default.
- W4384705423 isParatext "false" @default.
- W4384705423 isRetracted "false" @default.
- W4384705423 workType "article" @default.