Matches in SemOpenAlex for { <https://semopenalex.org/work/W4376456181> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4376456181 endingPage "163" @default.
- W4376456181 startingPage "144" @default.
- W4376456181 abstract "Massive Multiple-Input Multiple-Output (M-MIMO) uses hundreds of antennas in mobile communications base stations to increase the amount of transmitted data and the number of connected devices in 5G and beyond. However, M-MIMO systems increase the complexity of recovering the transmitted data (detection phase). To address this challenge, we leverage low-precision arithmetic in recent NVIDIA GPUs to improve the latency/scalability/accuracy of M-MIMO detection. We propose a GPU tree-based detection algorithm that aggregates multiple tree levels and formulates the computation as a matrix multiplication operation followed by a square-norm calculation and sorting (reduction) phase. This process is repeated until reaching the last level of the detection tree. The obtained results show near-optimal data detection with a 10 $$times $$ speedup compared to a two-socket 28-core IceLake CPU implementation. We further deploy low-precision arithmetic operations. We show that moving from single-precision 32-bit floating-point arithmetic (FP32) to half-precision 16-bit representation (FP16) does not affect the accuracy performance while translating into an additional 1.7 $$times $$ speedup. In addition, exploiting 8-bit integer representation results in an acceptable error rate degradation that can be compensated by increasing the number of aggregated levels. In addition, we propose a multi-GPU version that computes the matrix-multiplication operation of subsequent iterations in parallel. This latter operation represents more than 80% of the elapsed time for dense constellations. Results with four A100 GPUs show an additional 2.3 $$times $$ relative speedup compared to our single GPU version. The achieved accuracy/scalability balance may accelerate the deployment of this technology and promote low-precision GPU computations within the wireless communication community." @default.
- W4376456181 created "2023-05-14" @default.
- W4376456181 creator A5008189935 @default.
- W4376456181 creator A5015776910 @default.
- W4376456181 creator A5017526753 @default.
- W4376456181 creator A5021283893 @default.
- W4376456181 creator A5083193286 @default.
- W4376456181 date "2023-01-01" @default.
- W4376456181 modified "2023-10-01" @default.
- W4376456181 title "GPU-Based Low-Precision Detection Approach for Massive MIMO Systems" @default.
- W4376456181 cites W1570615599 @default.
- W4376456181 cites W1997002146 @default.
- W4376456181 cites W2116631972 @default.
- W4376456181 cites W2133475491 @default.
- W4376456181 cites W2140940105 @default.
- W4376456181 cites W2156787051 @default.
- W4376456181 cites W2493056561 @default.
- W4376456181 cites W2897534136 @default.
- W4376456181 doi "https://doi.org/10.1007/978-3-031-32041-5_8" @default.
- W4376456181 hasPublicationYear "2023" @default.
- W4376456181 type Work @default.
- W4376456181 citedByCount "0" @default.
- W4376456181 crossrefType "book-chapter" @default.
- W4376456181 hasAuthorship W4376456181A5008189935 @default.
- W4376456181 hasAuthorship W4376456181A5015776910 @default.
- W4376456181 hasAuthorship W4376456181A5017526753 @default.
- W4376456181 hasAuthorship W4376456181A5021283893 @default.
- W4376456181 hasAuthorship W4376456181A5083193286 @default.
- W4376456181 hasConcept C11413529 @default.
- W4376456181 hasConcept C114614502 @default.
- W4376456181 hasConcept C121332964 @default.
- W4376456181 hasConcept C127162648 @default.
- W4376456181 hasConcept C17349429 @default.
- W4376456181 hasConcept C173608175 @default.
- W4376456181 hasConcept C207987634 @default.
- W4376456181 hasConcept C2780595030 @default.
- W4376456181 hasConcept C31258907 @default.
- W4376456181 hasConcept C33923547 @default.
- W4376456181 hasConcept C41008148 @default.
- W4376456181 hasConcept C48044578 @default.
- W4376456181 hasConcept C62520636 @default.
- W4376456181 hasConcept C68339613 @default.
- W4376456181 hasConcept C77088390 @default.
- W4376456181 hasConcept C84114770 @default.
- W4376456181 hasConceptScore W4376456181C11413529 @default.
- W4376456181 hasConceptScore W4376456181C114614502 @default.
- W4376456181 hasConceptScore W4376456181C121332964 @default.
- W4376456181 hasConceptScore W4376456181C127162648 @default.
- W4376456181 hasConceptScore W4376456181C17349429 @default.
- W4376456181 hasConceptScore W4376456181C173608175 @default.
- W4376456181 hasConceptScore W4376456181C207987634 @default.
- W4376456181 hasConceptScore W4376456181C2780595030 @default.
- W4376456181 hasConceptScore W4376456181C31258907 @default.
- W4376456181 hasConceptScore W4376456181C33923547 @default.
- W4376456181 hasConceptScore W4376456181C41008148 @default.
- W4376456181 hasConceptScore W4376456181C48044578 @default.
- W4376456181 hasConceptScore W4376456181C62520636 @default.
- W4376456181 hasConceptScore W4376456181C68339613 @default.
- W4376456181 hasConceptScore W4376456181C77088390 @default.
- W4376456181 hasConceptScore W4376456181C84114770 @default.
- W4376456181 hasLocation W43764561811 @default.
- W4376456181 hasOpenAccess W4376456181 @default.
- W4376456181 hasPrimaryLocation W43764561811 @default.
- W4376456181 hasRelatedWork W109452172 @default.
- W4376456181 hasRelatedWork W1634487624 @default.
- W4376456181 hasRelatedWork W1830101842 @default.
- W4376456181 hasRelatedWork W2004686618 @default.
- W4376456181 hasRelatedWork W2034045337 @default.
- W4376456181 hasRelatedWork W2370911386 @default.
- W4376456181 hasRelatedWork W2392023973 @default.
- W4376456181 hasRelatedWork W2566157299 @default.
- W4376456181 hasRelatedWork W2997952415 @default.
- W4376456181 hasRelatedWork W3176814699 @default.
- W4376456181 isParatext "false" @default.
- W4376456181 isRetracted "false" @default.
- W4376456181 workType "book-chapter" @default.