Abstract: Some embodiments of the invention provide a novel method for programming the management, control and data planes of a software-defined network (SDN) in a unified way. Some embodiments use a transactional database to store the management plane state, and implement the control plane with a specialized query language that, when compiled, automatically executes in an incremental fashion, which improves the scalability of the control plane. For instance, in response to a change, the controller does not re-compute and redistribute the entire network state. Instead, it performs an incremental amount of work proportional to the size of modified state, not of the entire network state. Some embodiments use Differential Datalog (DDlog) for the control plane to compute over relations and collections, and to offer automatic incremental updates. To aid correctness, some embodiments type-check together the management, control and data planes, and use automated tools to generate most code for data movement between planes.

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document).

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document).

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document).

Abstract: Query models for document sets (such as XML documents or records in a relational database) typically involve a schema defining the structure of the documents. However, rigidly defined schemas often raise difficulties with document validation with even inconsequential structural variations. Additionally, queries developed against schema-constrained documents are often sensitive to structural details and variations that are not inconsequential to the query, resulting in inaccurate results and development complications, and that may break upon schema changes. Instead, query models for hierarchically structured documents that enable “twig” queries specifying only the structural details of document nodes that are relevant to the query (e.g., students in a student database having a sibling named “Lee” and a teacher named “Smith,” irrespective of unrelated structural details of the document).

Abstract: A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.

Abstract: Instruction set architecture (ISA) extension support is described for control-flow integrity (CFI) and for XFI memory protection. ISA replaces CFI guard code with single instructions. ISA support is provided for XFI in the form of bounds-check instructions. Compared to software guards, hardware support for CFI and XFI increases the efficiency and simplicity of enforcement. In addition, the semantics for CFI instructions allows more precise static control-flow graph encodings than were possible with a prior software CFI implementation.

Abstract: A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.

Abstract: Software control flow integrity is provided by embedding identifying bit patterns at computed control flow instruction sources and destinations. The sources and destinations of computed control flow instructions are determined with reference to a control flow graph. The identifying bit patterns are compared during software execution, and a match between a source and a respective destination ensures control flow consistent with the control flow graph. Security measures are implemented when the comparison results in a mismatch, indicating that control flow has deviated from the anticipated course.

Abstract: Instruction set architecture (ISA) extension support is described for control-flow integrity (CFI) and for XFI memory protection. ISA replaces CFI guard code with single instructions. ISA support is provided for XFI in the form of bounds-check instructions. Compared to software guards, hardware support for CFI and XFI increases the efficiency and simplicity of enforcement. In addition, the semantics for CFI instructions allows more precise static control-flow graph encodings than were possible with a prior software CFI implementation.

Abstract: A general purpose high-performance distributed execution engine for coarse-grained data-parallel applications is proposed that allows developers to easily create large-scale distributed applications without requiring them to master concurrency techniques beyond being able to draw a graph of the data-dependencies of their algorithms. Based on the graph, a job manager intelligently distributes the work load so that system resources are used efficiently. The system is designed to scale from a small cluster of a few computers, or the multiple CPU cores on a powerful single computer, up to a data center containing thousands of servers.

Abstract: Software memory access control is provided by associating instruction areas with memory areas such that instruction areas are not permitted to access memory areas with which they are not associated. Checks may be inserted in the instruction areas to ensure that data provided by a memory group is provided by an associated memory area. Additionally, control flow integrity for the instruction areas may be provided by embedding identifying bit patterns within computed control flow instructions contained in the instruction groups. In this way, control flow of the instruction areas may be provided, thus preventing diversion of control flow and minimizing required checks.

Abstract: Software memory access control is provided by associating instruction areas with memory areas such that instruction areas are not permitted to access memory areas with which they are not associated. Checks may be inserted in the instruction areas to ensure that data provided by a memory group is provided by an associated memory area. Additionally, control flow integrity for the instruction areas may be provided by embedding identifying bit patterns within computed control flow instructions contained in the instruction groups. In this way, control flow of the instruction areas may be provided, thus preventing diversion of control flow and minimizing required checks.

Abstract: Software control flow integrity is provided by embedding identifying bit patterns at computed control flow instruction sources and destinations. The sources and destinations of computed control flow instructions are determined with reference to a control flow graph. The identifying bit patterns are compared during software execution, and a match between a source and a respective destination ensures control flow consistent with the control flow graph. Security measures are implemented when the comparison results in a mismatch, indicating that control flow has deviated from the anticipated course.