Microsoft Technology Licensing, LLC

Vulcan Portals Inc.

Supercede, Inc.

Vulcan Inc.

Mercata, Inc.

Instantations, Inc.

Zhigu Holdings Limited

Niklas Gustafsson

Paul F Ringseth

Genevieve Fernandes

William Robert Messmer

Joshua Phillips

Artur Laksberg

John Joseph Duffy

David S Callahan

Mads Torgersen

Tom Van Horn

Richard V Halbert

Dale A Woodford

Rick Molloy

John Hamby

Henricus Johannes Maria Meijer

Stephen Harris Toub

Vance Palmer Morrison

Geoffrey M Kizer

John Lawrence Hamby

Philip Lucido

Marko Radmilac

Neal M Gafter

Patrick Lau

John M Thrun

Anders Hejlsberg

Joseph L Hellerstein

Matthew J Warren

Patrick James Helland

David Paul Hill

Bradley Michael Waters

John Joseph Rivard

Zlatko Michailov

Jason P Allen

Dmitry Lomov

Lucian Wischik

Rahul V Patil

Daniela Cristina Manu

Jerome P Pache

Greg C Dean

Jon C Engman

Rahul Patil

Paul Ringseth

Fine-grained parallelism within isolated object graphs is used to provide safe concurrent operations within the isolated object graphs. One example provides an abstraction labeled IsolatedObjectGraph that encapsulates at least one object graph, but often two or more object graphs, rooted by an instance of a type member. By encapsulating the object graph, no references from outside of the object graph are allowed to objects inside of the object graph. Also, the encapsulated object graph does not contain references to objects outside of the graphs. The isolated object graphs provide for safe data parallel operations, including safe data parallel mutations such as foreach loops. In an example, the ability to isolate the object graph is provided through type permissions.

Concurrent mutation of isolated object graphs

A method and/or computer program that incorporates isolation principles of separate address spaces and enforces the principles with a compiler and supporting runtime through a language-based model is disclosed. This approach significantly lowers the required overhead and retains the beneficial qualities of the scalable, isolated model. The model is implemented in a programming language where memory-based state is partitioned into a plurality of domains where the variables inside of a domain are isolated from external components. Agents are introduced inside of the domain and act on behalf of clients outside of the domain. The agents communicate with their clients via message-passing to enforce the isolation of the domain state. The domain-based isolation addresses the partitioning of memory-based state without the introduction of separate processes. Domains can also be used in conjunction with a distributed model either within a single computing device or between computing devices.

Language-based model for isolating shared state

A language-based model to support asynchronous operations set forth in a synchronous syntax is provided. The asynchronous operations are transformed in a compiler into an asynchronous pattern, such as an APM-based pattern (or asynchronous programming model based pattern). The ability to compose asynchronous operations comes from the ability to efficiently call asynchronous methods from other asynchronous methods, pause them and later resume them, and effectively implementing a single-linked stack. One example includes support for ordered and unordered compositions of asynchronous operations. In an ordered composition, each asynchronous operation is started and finished before another operation in the composition is started. In an unordered composition, each asynchronous operation is started and completed independently of the operations in the unordered composition.

Language-based model for asynchronous operations

Fine-grained parallelism within isolated object graphs is used to provide safe concurrent operations within the isolated object graphs. One example provides an abstraction labeled IsolatedObjectGraph that encapsulates at least one object graph, but often two or more object graphs, rooted by an instance of a type member. By encapsulating the object graph, no references from outside of the object graph are allowed to objects inside of the object graph. Also, the encapsulated object graph does not contain references to objects outside of the graphs. The isolated object graphs provide for safe data parallel operations, including safe data parallel mutations such as for each loops. In an example, the ability to isolate the object graph is provided through type permissions.

An interface between a resource manager and schedulers in a process executing on a computer system allows the resource manager to manage the resources of the schedulers. The resource manager communicates with the schedulers using the interface to access statistical information from the schedulers. The statistical information describes the amount of use of the resources by the schedulers. The resource manager also communicates with the schedulers to dynamically allocate and reallocate resources among the schedulers in the same or different processes or computer systems in accordance with the statistical information.

Interface between a resource manager and a scheduler in a process

A process in a computer system creates and uses a meta-scheduler with meta-contexts that execute on meta-virtual processors. The meta-scheduler includes a set of schedulers with scheduler-contexts that execute on virtual processors. The meta-scheduler schedules the scheduler-contexts on the meta-contexts and schedules the meta-contexts on the meta-virtual processors which execute on execution contexts associated with hardware threads.

Meta-scheduler with meta-contexts

Unsuspended co-routines are handled by the machine call stack mechanism in which the stack grows and shrinks as recursive calls are made and returned from. When a co-routine is suspended, however, additional call stack processing is performed. A suspension message is issued, and the entire resume-able part of the call stack is removed, and is copied to the heap. A frame that returns control to a driver method (a resumer) is copied to the call stack so that resumption of the co-routine does not recursively reactivate the whole call stack. Instead the resumer reactivates only the topmost or most current frame called the leaf frame. When a co-routine is suspended, it does not return to its caller, but instead returns to the resumer that has reactivated it.

Efficient resumption of co-routines on a linear stack

A scheduler in a process of a computer system schedules tasks of a task group for concurrent execution by multiple execution contexts. The scheduler provides a mechanism that allows the task group to be cancelled by an arbitrary execution context or an asynchronous error state. When a task group is cancelled, the scheduler sets a cancel indicator in each execution context that is executing tasks corresponding to the cancelled task group and performs a cancellation process on each of the execution contexts where a cancel indicator is set. The scheduler also creates local aliases to allow task groups to be used without synchronization by execution contexts that are not directly bound to the task groups.

Cancellation mechanism for cancellable tasks including stolen task and descendent of stolen tasks from the cancellable taskgroup

The present invention extends to methods, systems, and computer program products for transforming source code to await execution of asynchronous operations. Embodiments of the invention simplify authoring and use of asynchronous methods, by generating statements that use well-defined awaitable objects to await completion of asynchronous operations. For example, a computer system can transform a statement that requests to await the completion of an asynchronous operation into a plurality of statements that use a predefined pattern of members of an awaitable object corresponding the asynchronous operation. The pattern can include one or more members configured to return a completion status of the asynchronous operation, one or more members configured to resume execution of the asynchronous method at a resumption point when the asynchronous operation completes, and one or more members configured to retrieve completion results. Accordingly, the plurality of statements can use these members to await execution of the asynchronous operation.

Pattern-based compilation of asynchronous consumption

Local storage may be allocated for each processing resource in a process of a computer system. Each processing resource may be virtualized and may have a one-to-one or a many-to-one correspondence with with physical processors. The contents of each local storage persist across various execution contexts that are executed by a corresponding processing resource. Each local storage may be accessed without synchronization (e.g., locks) by each execution context that is executed on a corresponding processing resource. The local storages provide the ability to segment data and store and access the data without synchronization. The local storages may be used to implement lock-free techniques such as a generalized reduction where a set of values is combined through an associative operator.

Persistent local storage for processor resources

One embodiment includes a method of performing dataflow processing. The method includes representing a first asynchronous processing node as a first future. The first future represents the lifecycle of processing of the first asynchronous processing node. The method further includes representing one or more other asynchronous operations as one or more other futures. The one or more other futures represent the asynchronous completion of one or more operations'processing. The first future and the one or more other futures are represented as a single composite future. The single composite future represents completion of processing of the combination of the first asynchronous processing node and the one or more other asynchronous operations.

Cancelable and faultable dataflow nodes

Each processing resource in a scheduler of a process executing on a computer system maintains counts of the number of tasks that arrive at the processing resource and the number of tasks that complete on the processing resource. The counts are maintained in storage that is only writeable by the corresponding processing resource. The scheduler collects and sums the counts from each processing resource and provides statistics based on the summed counts and previous summed counts to a resource manager in response to a request from the resource manager. The scheduler does not reset the counts when the counts are collected and stores copies of the summed counts for use with the next request from the resource manager. The counts may be maintained without synchronization and with thread safety to minimize the impact of gathering statistics on the application.

Monitoring and updating tasks arrival and completion statistics without data locking synchronization

Multiple types of executable agents operating within a domain. The domain includes mutable shared state and immutable shared state, with agents internal to the domain only operating on the shared state. Writer agents are defined to be agents that have read access and write access to mutable shared state and read access only to immutable shared state. General reader agents have read access to both mutable shared state and immutable shared state and have no write access. Immutable reader agents have read access to only immutable shared state and have no write access. By appropriate scheduling of the different types of agents, data races may be reduced or eliminated.

Method for managing data accessibility by scheduling three types of executable agents associated with pre-defined access rights within a domain

A runtime environment of a computer system is provided that creates first and second scheduler instances in a process. Each scheduler instance includes allocated processing resources and is assigned a set of tasks for execution. Each scheduler instance schedules tasks for execution using the allocated processing resources to perform the work of the process.

Method of assigning instructions in a process to a plurality of scheduler instances based on the instruction, in which each scheduler instance is allocated a set of negoitaited processor resources

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Bellevue, WA, United States of America

Niklas Gustafsson