LF_DPDK17_Abstract APIs for DPDK and ODP
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This document discusses abstract interfaces, APIs, and implementations for network functions like IPsec. It proposes a common Network Application Interface to provide hardware independence and allow live migration of virtual network functions between platforms with and without acceleration. This interface could be realized by both the Open Data Plane (ODP) and DPDK APIs/implementations to unify their approaches for network functions like IPsec processing.
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LCU14 310- Cisco ODP
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Speaker: Robbie King
Date: September 17, 2014
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★ Session Summary ★
Cisco to present their experience using ODP to provide portable accelerated access to crypto functions on various SoCs.
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★ Resources ★
Zerista: http://lcu14.zerista.com/event/member/137757
Google Event: https://plus.google.com/u/0/events/ckmld1hll5jjijq11frbqmptet8
Video: https://www.youtube.com/watch?v=eFlTmslVK-Y&list=UUIVqQKxCyQLJS6xvSmfndLA
Etherpad: http://pad.linaro.org/p/lcu14-310
---------------------------------------------------
★ Event Details ★
Linaro Connect USA - #LCU14
September 15-19th, 2014
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http://www.linaro.org
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Speaker: Bill Fischofer
Date: February 9, 2015
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★ Session Summary ★
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--------------------------------------------------
★ Resources ★
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Etherpad: http://pad.linaro.org/p/hkg15-110
---------------------------------------------------
★ Event Details ★
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Regal Airport Hotel Hong Kong Airport
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http://www.linaro.org
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Iirdem design and implementation of finger writing in air by using open cv (c...
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DPDK's micro-benchmarks are important to run prior to application development and benchmarking. They quantitatively measure the performance of key high performance objects and operations in DPDK like rings, memory pools, mbufs, and functions like memory copying and hashing. This helps optimize the system configuration and ensures cores and devices are allocated optimally across sockets before developing applications. The document demonstrates some examples of DPDK micro-benchmarks and encourages attendees to find and use them to build a strong performance foundation.
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The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.inQuba Webinar Mastering Customer Journey Management with Dr Graham Hill
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In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
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