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GTC ON-DEMAND

Presentation
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Abstract:

The dollar treasury and futures market is arguably the most liquid and actively traded market in the world. On a daily basis, this market generates hundreds of millions of records of data, and the set of securities involved amounts to thousands. The environment is dynamic, interrelated, and fast-paced, and liquidity conditions are constantly changing. As participants engage in strategies, enter and exit this marketplace, certain relationships capture the attention of various participants, who apply capital to their (sometimes machine-learned) convictions. Moreover, correlations are non static and exhibit a term structure. Instead of making a single static model, we will explore how using Multi-GPU setups and this large streaming dataset, you can set up an online machine learning environment where thousands of strategies can be monitored and pockets of available liquidity uncovered.

The dollar treasury and futures market is arguably the most liquid and actively traded market in the world. On a daily basis, this market generates hundreds of millions of records of data, and the set of securities involved amounts to thousands. The environment is dynamic, interrelated, and fast-paced, and liquidity conditions are constantly changing. As participants engage in strategies, enter and exit this marketplace, certain relationships capture the attention of various participants, who apply capital to their (sometimes machine-learned) convictions. Moreover, correlations are non static and exhibit a term structure. Instead of making a single static model, we will explore how using Multi-GPU setups and this large streaming dataset, you can set up an online machine learning environment where thousands of strategies can be monitored and pockets of available liquidity uncovered.

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Topics:
Finance - Deep Learning, Deep Learning & AI Frameworks
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9178
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Speakers:
Peter Decrem
- Quantifi
Abstract:
Quantifi will demo its xLDevelopment environment, which provide developers with an easy to use development environment which allows cuda functionality to be in Microsoft Excel. With as little as four lines, one will also select the position of the function in the menu bar, xml markup language will display in the excel help functionality, and objects can be easily added to the object cache. These objects can then be inspected by the end user or developer. Performance information can also be displayed in the object cache. The environment provides the developer an environment where he can focus on developing high performance functionality, and all intermediate layers of interface are taking care of by the environment.
Quantifi will demo its xLDevelopment environment, which provide developers with an easy to use development environment which allows cuda functionality to be in Microsoft Excel. With as little as four lines, one will also select the position of the function in the menu bar, xml markup language will display in the excel help functionality, and objects can be easily added to the object cache. These objects can then be inspected by the end user or developer. Performance information can also be displayed in the object cache. The environment provides the developer an environment where he can focus on developing high performance functionality, and all intermediate layers of interface are taking care of by the environment.  Back
 
Topics:
Tools & Libraries, Finance
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S102297
Streaming:
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Speakers:
Peter Decrem
Abstract:

Learn how to compute traditional end of day computations in real time through the use of a hybrid GPU/CPU computing environment. We will detail how computing intensive tasks are delegated to the GPU while interface issues are dealt with by the CPU. We will discuss our methodology consisting of the following three components: (1) valuations; (2) by tenor risk measures; and (3) full distributions allowing for more complex analytics such as exotic options products valuation and counterparty value adjustments calculation.

Learn how to compute traditional end of day computations in real time through the use of a hybrid GPU/CPU computing environment. We will detail how computing intensive tasks are delegated to the GPU while interface issues are dealt with by the CPU. We will discuss our methodology consisting of the following three components: (1) valuations; (2) by tenor risk measures; and (3) full distributions allowing for more complex analytics such as exotic options products valuation and counterparty value adjustments calculation.

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Topics:
Finance, Developer - Algorithms, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S10040
Streaming:
Download:
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