PPT-Extensible Kernels

Exokernel and SPIN Presented by Hakim Weatherspoon Based on slides from Edgar Velázquez Armendáriz and Ken Birman 2 Traditional OS services Management and Protection Provides a set of abstractions. g BinetCauchy kernels However such approaches are only applicable to time series data living in a Euclidean space eg joint trajectories extracted from motion capture data or feature point trajectories extracted from video Much of the success of rec Edgar Velázquez-Armendáriz. September. 24. th. 2009. Agenda. Exokernel. : An Operating System architecture for Application-Level Resource Management. Extensibility, Safety and Performance in the . Also known as “meta-data”. April 2016. Comments in SPICE Kernels. 2. Comments, also called “meta-data,” are information that describe the context of kernel data, i.e. “data about data”. Comments are provided inside kernels as plain text (prose). April 2016. Porting Kernels. 2. Porting Issues - 1. Data formats vary across platforms, so data files created on platform “X” may not be usable on platform “Y.”. Binary. . formats. : different platforms use different bit patterns to represent numbers (and possibly characters).. Úlfar Erlingsson, Google Inc.. Marcus . Peinado. , Microsoft Research. Simon Peter, Systems Group, ETH Zurich. Mihai. . Budiu. , Microsoft Research. 1. Fay. Wouldn’t it be nice if…. We could know what our clusters were doing?. Úlfar Erlingsson, Google Inc.. Marcus . Peinado. , Microsoft Research. Simon Peter, Systems Group, ETH Zurich. Mihai. . Budiu. , Microsoft Research. 1. Fay. Wouldn’t it be nice if…. We could know what our clusters were doing?. April 2016. Agenda. Overview. Kernel architecture. Producing kernels. Using kernels. Introduction to Kernels. 2. Introduction to Kernels. 3. What is a SPICE “Kernel”. “Kernel” means file. “Kernel” means a file . Ross McIlroy, Chris Hawblitzel, Galen Hunt. Microsoft Research. Helios: Heterogeneous Multiprocessing with Satellite Kernels. 1. Problem: HW now heterogeneous. Heterogeneity . ignored. by operating systems. Corporate Profile. Engrave Overview . Reliable | Scalable | Extensible | Future-Proof | Best ROI | Best Technology Partner . Products . Reliable | Scalable | Extensible | Future-Proof | Best ROI | Best Technology Partner . Perceptrons. The . perceptron. A. B. instance. . x. i. Compute: . y. i. = . sign(. v. k. . . . x. i. . ). ^. y. i. ^. y. i. If mistake: . v. k+1. = . v. k. + . y. i. . x. i. . x . is a vector. Pipeline . Parallelism from . Multiple . Dependent Kernels for . GPUs. Gwangsun Kim, . Jiyun Jeong, John Kim. Mark Stephenson. GPU Background. CTA. Kernel grid. CTA (Cooperative Thread Array). or Thread block. and . Distributional. Semantics. :. Between. . Syntactic. . Structures. and . Compositional. . Distributional. Semantics. Fabio Massimo . Zanzotto. ART Group. Dipartimento di Ingegneria dell’Impresa. Evaluation in Database Systems. Justin J. . Levandoski. Mohamed F. . Mokbel. Mohamed E. . Khalefa. Talk Outline. Preference Methods. Implementing Preference Methods in a DBMS. The Challenge: Extensible Preference Evaluation. Jeremy Tammik. Principal Developer Consultant. About the Presenter. Jeremy Tammik. Principal Developer Consultant. Developer Technical Services. EMEA, Autodesk SARL. Jeremy is a member of the AEC workgroup of the Autodesk Developer Network ADN team, providing developer support, training, conference presentations, and blogging on the Revit API..