Monthly Archives: June 2019

Network Services in a Multi-Vendor Environment

Monday, July 15, 2019, 6:30 PM – 9:00 PM PDT

The event is FREE. Food & drinks will be provided.

This event is organized by:

 Co-sponsors:

 Speaker1: Saikrishna Kotha
                       Director, Global Network Engineering

Speaker2: Anand Palaniswamy
                       Sr. Manager, Cloud Engineering at PayPal

Location: PayPal Town Hall, 2161 N 1st St. San Jose, CA 95131  View Map  

(Register here)

PROGRAM:

  • 6:30 – 7:00 PM Registration, Pizza, Networking & Refreshments
  • 7:00 – 8:30PM Technical Talks
  • 8:30 – 8:50PM Q&A/Adjourn
  • 9:00PM everybody must vacate the building 

1) Speaker1:

Abstract:
Core Network Services provides network connectivity for PayPal site infrastructure. To address 5 9s’ site reliability goals, the demand for network to perform at its best keeps growing. PayPal transformed its data center networks by deploying white-box leaf/spine designs to help with horizontal scaling, low latency, and resilience to failures. By developing common framework layer, PayPal is able to address network automation/service API needs in multi-vendor environment. Saikrishna will discuss the design approach, lessons learned and how various vendor technologies are leveraged in this transformation process.

Bio: Saikrishna Kotha

Saikrishna has 20 years of technology leadership and management experience in networking domain spanning across optical, wireless, and wired technologies. Saikrishna’s recent focus has been implementing web scale Datacenter networking technologies. Currently he leads PayPal’s Core Network Services organization. Prior to PayPal, Saikrishna worked at LinkedIn where he was instrumental in building white-box network switches. He also worked at Dell, Xilinx, Tasman Networks (acquired by Nortel) and Ciena. Saikrishna holds 12 issued patents and 15 pending in converged storage/networking technologies, SDN and NFV domains. Saikrishna holds MBA from TAMU-commerce and Bachelor’s degree in ECE from Andhra University, India.
 LinkedIn profile: https://www.linkedin.com/m/profile/saikrishnakotha/

2) Speaker2:

Abstract:
Core Network Services provides network connectivity for PayPal site infrastructure. To address 5 9s’ site reliability goals, the demand for network to perform at its best keeps growing. PayPal transformed its data center networks by deploying white-box leaf/spine designs to help with horizontal scaling, low latency, and resilience to failures. By developing common framework layer, PayPal is able to address network automation/service API needs in multi-vendor environment. Saikrishna will discuss the design approach, lessons learned and how various vendor technologies are leveraged in this transformation process.

Bio: Anand Palaniswamy

Anand has 18+ years of experience and works at PayPal for last 7 years. Currently, he is focused on building APIs to enable self-service capabilities for PayPal Core Network Services and he was leading Cloud Software Engineering team for building PayPal private cloud. Prior to PayPal, he was part of eBay for an year and worked for Tellabs where he was building frameworks and platform for Network Management System. Anand received his Master’s degree in Computer Science from University of Madras.

Open to all to attend

(Online registration is needed. If you did not register, seating is not guaranteed.)

Eventbrite - enabling-digital-transformation-at-the-edge
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Squeezing down the computing requirements of deep neural networks

Wednesday, July 24, 2019, 6:00 PM – 8:00 PM PDT  

The event is FREE. Food & drinks will be provided.

This event is organized by:

 Co-sponsors:

Speaker1:  Forrest Iandola, CEO and co-Founder of DeepScale

Speaker2: Albert Shaw, Engineer at DeepScale

Location: 673 South Milpitas Blvd. Milpitas, CA 95035, USA  View Map 

(Register here)

PROGRAM:

  • 6:00 – 6:30 PM Networking & Refreshments
  •  6:30 – 7:30 PM Talk
  • 7:30 – 8:00 PM Q&A/Adjourn

Abstract: Deep Neural Networks (DNNs) have enabled breakthrough levels of accuracy on a variety of tasks in vision, audio, and text. However, DNNs can be quite computationally-intensive, and highly-accurate DNNs often require a full-sized GPU server for real-time inference. To squeeze DNNs into smaller computing footprints, there are a number of techniques, including better DNN design, DNN quantization, better implementations of DNNs, and better utilization of specialized computing hardware. This talk touches on all these techniques, with particular focus on better DNN design for computer vision. Recently, Neural Architecture Search (NAS) technologies have begun to make significant progress in automating the process of designing “squeezed” DNNs, and we cover some of the latest work on NAS in this talk.

Bio: Forrest Iandola  

Forrest Iandola completed a PhD in Electrical Engineering and Computer Science at UC Berkeley, where his research focused on improving the efficiency of deep neural networks (DNNs). His best-known published research ranges from scaling DNN training to hundreds of GPUs (FireCaffe), to squeezing DNNs onto small edge-devices (SqueezeNet and SqueezeDet). His advances in scalable training and efficient inference of DNNs led to the founding of DeepScale, where he has been CEO since 2015. DeepScale builds energy-efficient vision and perception systems for automated vehicles.

Bio: Albert Shaw

Albert Shaw has been working on research in Neural Architecture Search (NAS) since 2017. He received his Masters in Computer Science from the Georgia Institute of Technology where he focused on speeding up Neural Architecture Search and creating more sample-efficient algorithms for Reinforcement Learning. At DeepScale, his work focuses on using NAS to develop state-of-the-art fast and accurate Deep Neural Networks for automated vehicle perception systems.

Open to all to attend

(Online registration is needed. If you did not register, seating is not guaranteed.)

Eventbrite - enabling-digital-transformation-at-the-edge

 

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[ValleyML.ai, IEEE SPS, CIS, CS, CAS] Hands-on OpenVX Inference Tutorial

[ValleyML.ai, IEEE SPS, CIS, CS, CAS] Hands-on OpenVX Inference Tutorial

Friday‎, ‎June‎ ‎14‎, ‎2019, ‎2‎:‎30‎ ‎PM to ‎5‎:‎30‎ ‎PM

IEEE CS SCV chapter is co-sponsoring this event as a relevant and beneficial to all our IEEE CS chapter members

Location: AMD Inc., 2485 Augustine Dr. Santa Clara, CA 95054

Event sponsored and organized by:

Co-sponsors:

Details & Registration at: https://www.eventbrite.com/e/ieee-sps-mivisionx-inference-tutorial-tickets-62540630710
Only limited seats are available for the tutorial. Book your tickets now at Eventbrite

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[ValleyML.ai, IEEE SCV-CIS and CS] AI, ML and Storage

[ValleyML.ai, IEEE SCV-CIS and CS] AI, ML and Storage

Hosted as a free event/open session for public as part of Flash Memory Summit on Wednesday, August 7th, 7pm to 9 pm

Organized by:

Sponsored by:

IEEE CS SCV is sponsoring this event as a relevant event for our members.

Register for a free exhibit pass at https://www.flashmemorysummit.com/

Free exhibit pass provides the access to exhibits, key notes and open
sessions.

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[ValleyML.ai] State of AI and ML-Summer 2019

[ValleyML.ai] State of AI and ML-Summer 2019

August 16, 9:00 AM – August 17, 6:00 PM PDT, @ Z-Park Silicon Valley, 4500 Great America Pkwy, Santa Clara, CA 95054, USA.

IEEE CS SCV is listing this event here as a relevant event for our members.

Join this 2-day event as part of series of regularly planned events to learn about the state-of-the-art advances in artificial intelligence (AI) and machine learning (ML) technology. Get IEEE PDH Certificate from IEEE Continuing Education.

Go to ValleyML.ai and hit register to go to Eventbrite page and use discount code VALLEYML_CS25 to get 25% off.

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Emergence of RISC-V computer architecture- embedded apps & ML acceleration

Emergence of RISC-V computer architecture- embedded apps & ML acceleration

 August 21 @ 7:00 pm9:00 pm, @ PayPal Town Hall, 2161 North First St. San Jose, CA 95131 View Map

 IEEE CS SCV is sponsoring this event as a relevant event for our members.

 Organized by:

Sponsored by:

§  IEEE Computer Society (CS) of Silicon Valley

 (Register here)

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