GTC ON-DEMAND

 
SEARCH SESSIONS
SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Presentation
Media
Abstract:
Investigating events and transactions is critical to operational teams such as IT, security, fraud, and increasingly even sales, marketing, fintech, and logistics. But as organizations gather more data to improve their visibility to these operations, it becomes more difficult to surface structure and follow promising threads. We'll discuss two complementary techniques that are changing what is practical. GPU computing is solving the problem of interactivity-at-scale, and graph systems are enabling teams to reason about correlations across their data. Using examples from malware outbreaks to human trafficking to netflows, we'll demonstrate the kind of visual experiences that are now viable. Throughout, we will touch on supporting technologies from the GPU Open Analytics Initiative ecosystem and how Graphistry leverages them for our 2.0 engine.
Investigating events and transactions is critical to operational teams such as IT, security, fraud, and increasingly even sales, marketing, fintech, and logistics. But as organizations gather more data to improve their visibility to these operations, it becomes more difficult to surface structure and follow promising threads. We'll discuss two complementary techniques that are changing what is practical. GPU computing is solving the problem of interactivity-at-scale, and graph systems are enabling teams to reason about correlations across their data. Using examples from malware outbreaks to human trafficking to netflows, we'll demonstrate the kind of visual experiences that are now viable. Throughout, we will touch on supporting technologies from the GPU Open Analytics Initiative ecosystem and how Graphistry leverages them for our 2.0 engine.  Back
 
Topics:
Cyber Security, Accelerated Data Science
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9813
Streaming:
Download:
Share:
 
Abstract:

Investigation teams have a love/hate relationship with event logs. The ever-increasing volumes and richness of data opens many possibilities, but also makes day-to-day operations a slog. GPU acceleration is changing basic assumptions around what is possible. From incident response and threat hunting to anti-money-laundering and anti-fraud, Graphistry has been working with F500 and federal teams on more scalable approaches to human-in-the-loop analytics. In particular, we have been bringing end-to-end GPU acceleration to visual graph analytics for visually connecting virtually any log data. Using examples from malware outbreaks to human trafficking, we'll demonstrate what can now be achieved, and dig into the supporting technologies like hypergraphs, Apache Arrow, GoAi, and visual playbooks.

Investigation teams have a love/hate relationship with event logs. The ever-increasing volumes and richness of data opens many possibilities, but also makes day-to-day operations a slog. GPU acceleration is changing basic assumptions around what is possible. From incident response and threat hunting to anti-money-laundering and anti-fraud, Graphistry has been working with F500 and federal teams on more scalable approaches to human-in-the-loop analytics. In particular, we have been bringing end-to-end GPU acceleration to visual graph analytics for visually connecting virtually any log data. Using examples from malware outbreaks to human trafficking, we'll demonstrate what can now be achieved, and dig into the supporting technologies like hypergraphs, Apache Arrow, GoAi, and visual playbooks.

  Back
 
Topics:
Cyber Security, Accelerated Data Science
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8184
Streaming:
Share:
 
Abstract:
This talk shares how GPUs are enabling investigation teams to answer tough event data questions around progression, scope, root cause, patterns, and anomalies. Most of these problems are equivalent to analyzing graphs for correlations. Drawing examples from areas like cybersecurity, we share how to think about event data as a graph problem, and how scaling graph visualization and analytics with GPUs is enabling investigation teams to unlocks new insights and workflows. In particular, we show: -- Correlating events with hypergraphs, such as for killchain analysis and identifying shell companies -- Visualizing large graphs with GPU rendering and smart designs -- Fast analytics through GPU cloud computing -- Combining the above into daily operational workflows for data scientists, developers, and front-line analysts We draw examples from Graphistry's work in the Fortune 500 and the US government.
This talk shares how GPUs are enabling investigation teams to answer tough event data questions around progression, scope, root cause, patterns, and anomalies. Most of these problems are equivalent to analyzing graphs for correlations. Drawing examples from areas like cybersecurity, we share how to think about event data as a graph problem, and how scaling graph visualization and analytics with GPUs is enabling investigation teams to unlocks new insights and workflows. In particular, we show: -- Correlating events with hypergraphs, such as for killchain analysis and identifying shell companies -- Visualizing large graphs with GPU rendering and smart designs -- Fast analytics through GPU cloud computing -- Combining the above into daily operational workflows for data scientists, developers, and front-line analysts We draw examples from Graphistry's work in the Fortune 500 and the US government.  Back
 
Topics:
Cyber Security, Accelerated Data Science, Data Center & Cloud Infrastructure
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7133
Download:
Share:
 
Abstract:
Deep learning and AI will revolutionize cybersecurity by dramatically improving detection and intrusion capabilities. However, we can't completely eliminate cyberthreats. We'll discuss how new AI technologies are working to enhance security, while also examining potential risks. We'll also discuss what role regulation should play in ensuring private institutions appropriately strike the right risk balance, and how government and industry are working together to combat cybercrimes.
Deep learning and AI will revolutionize cybersecurity by dramatically improving detection and intrusion capabilities. However, we can't completely eliminate cyberthreats. We'll discuss how new AI technologies are working to enhance security, while also examining potential risks. We'll also discuss what role regulation should play in ensuring private institutions appropriately strike the right risk balance, and how government and industry are working together to combat cybercrimes.  Back
 
Topics:
Leadership and Policy in AI, Cyber Security
Type:
Panel
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7223
Download:
Share:
 
Abstract:

Scaling visual investigations is a tough problem. Analysts in areas like cyber security, anti-fraud, ML model tuning, and network operations are struggling to see their data and how it connects. We'll discuss where visual graph analytics gets used and how Graphistry is dramatically streamlining the analyst experience. For example, when using visual graph models for exploring security event logs, we can load events around an incident and quickly determine the root cause, scope, and progression. We'll demonstrate how we solve three technical aspects of scaling visual graph analysis: streamlining investigation workflows, visualizing millions of events in the browser, and fast analytics. Core to our approach, our platform connects GPUs in the client to GPUs on the server. The result is an investigation experience that feels like a ""Netflix for data"" and can be used by anyone with a browser.

Scaling visual investigations is a tough problem. Analysts in areas like cyber security, anti-fraud, ML model tuning, and network operations are struggling to see their data and how it connects. We'll discuss where visual graph analytics gets used and how Graphistry is dramatically streamlining the analyst experience. For example, when using visual graph models for exploring security event logs, we can load events around an incident and quickly determine the root cause, scope, and progression. We'll demonstrate how we solve three technical aspects of scaling visual graph analysis: streamlining investigation workflows, visualizing millions of events in the browser, and fast analytics. Core to our approach, our platform connects GPUs in the client to GPUs on the server. The result is an investigation experience that feels like a ""Netflix for data"" and can be used by anyone with a browser.

  Back
 
Topics:
Accelerated Data Science, Federal, Data Center & Cloud Infrastructure
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7407
Download:
Share:
 
Abstract:

Enterprises "assume breach": someone, somewhere, already compromised them. Analysts sift through a GB/min (or more!) of attack logs from hundreds of thousands of systems. For every identified incident, they then map out the entire breach by backtracking through months of alerts. This talk shares how Graphistry and Accenture tackled the visual analytics problem: how do we explore big graphs? We'll drill into two of our GPU technologies for visualizing graphs: [1] StreamGL, our distributed real-time renderer for delivering buttery interactions, smart designs, and responsive analytics to standard web devices; [2] Node-OpenCL and our CLJS client: open source JavaScript libraries for server-side GPU scripting.

Enterprises "assume breach": someone, somewhere, already compromised them. Analysts sift through a GB/min (or more!) of attack logs from hundreds of thousands of systems. For every identified incident, they then map out the entire breach by backtracking through months of alerts. This talk shares how Graphistry and Accenture tackled the visual analytics problem: how do we explore big graphs? We'll drill into two of our GPU technologies for visualizing graphs: [1] StreamGL, our distributed real-time renderer for delivering buttery interactions, smart designs, and responsive analytics to standard web devices; [2] Node-OpenCL and our CLJS client: open source JavaScript libraries for server-side GPU scripting.

  Back
 
Topics:
Big Data Analytics, Aerospace and Defense, Professional Visualisation
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6114
Streaming:
Download:
Share:
 
Abstract:

GPUs are ushering in a new era of data visualization. Today, shoving one hundred thousand query results into a chart makes an illegible mess and kills interactivity. The good news is that infovis researchers invented smarter layouts that maximize visibility. The bad news is that these layouts and basic interactions are computationally intensive enough that analysts can no longer simply slide a slider, drag a graph cluster, etc. With the availability of GPUs, however, the rules have changed. This talk shows examples of smarter designs and how we use GPUs to turn them into interactive tools. For experts, we will discuss how running in browsers and even phones led to Graphistry's tiered GPU visualization engine approach, and touch on our use of WebGL, WebCL, and our own in-house libraries.

GPUs are ushering in a new era of data visualization. Today, shoving one hundred thousand query results into a chart makes an illegible mess and kills interactivity. The good news is that infovis researchers invented smarter layouts that maximize visibility. The bad news is that these layouts and basic interactions are computationally intensive enough that analysts can no longer simply slide a slider, drag a graph cluster, etc. With the availability of GPUs, however, the rules have changed. This talk shows examples of smarter designs and how we use GPUs to turn them into interactive tools. For experts, we will discuss how running in browsers and even phones led to Graphistry's tiered GPU visualization engine approach, and touch on our use of WebGL, WebCL, and our own in-house libraries.

  Back
 
Topics:
Big Data Analytics, Web Acceleration, Visualization - In-Situ & Scientific
Type:
Talk
Event:
GTC Silicon Valley
Year:
2015
Session ID:
S5589
Streaming:
Download:
Share:
 
 
Previous
  • Amazon Web Services
  • IBM
  • Cisco
  • Dell EMC
  • Hewlett Packard Enterprise
  • Inspur
  • Lenovo
  • SenseTime
  • Supermicro Computers
  • Synnex
  • Autodesk
  • HP
  • Linear Technology
  • MSI Computer Corp.
  • OPTIS
  • PNY
  • SK Hynix
  • vmware
  • Abaco Systems
  • Acceleware Ltd.
  • ASUSTeK COMPUTER INC
  • Cray Inc.
  • Exxact Corporation
  • Flanders - Belgium
  • Google Cloud
  • HTC VIVE
  • Liqid
  • MapD
  • Penguin Computing
  • SAP
  • Sugon
  • Twitter
Next