Efficient Execution of Irregular Dataflow Graphs Hardware/Software Co-optimization for Probabilistic AI and Sparse Linear Algebra /
This book focuses on the acceleration of emerging irregular sparse workloads, posed by novel artificial intelligent (AI) models and sparse linear algebra. Specifically, the book outlines several co-optimized hardware-software solutions for a highly promising class of emerging sparse AI models called...
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| Autors principals: | , , |
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| Autor corporatiu: | |
| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
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| Edició: | 1st ed. 2023. |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-031-33136-7 |
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Taula de continguts:
- Chapter 1. Irregular workloads at risk of losing the hardware lottery
- Chapter 2. Suitable data representation: A study of fixed point, floating point,and positTM formats for probabilistic AI
- Chapter 3. GraphOpt: constrained-optimization-based parallelization of irregular workloads for multicore processors
- Chapter 4. DAG Processing Unit version 1 (DPU): Efficient execution of irregular workloads on a multicore processor
- Chapter 5. DAG Processing Unit version 2 (DPU-v2): Efficient execution of irregular workloads on a spatial datapath
- Chapter 6. Conclusions and future work.