Azul Systems, Inc.

Google Inc.

Ivan Posva

Gil Tene

Daniel Dwight Grove

Michael A Wolf

Sanjay Ghemawat

Cliff N Click, Jr

Gautham K Thambidorai

Srdjan Petrovic

Matthew Rosencrantz

Tom Kraljevic

Jack H Choquette

Jeffrey Gee

Srdjan Mitrovic

Sivakumar Annamalai

Anirban Sengupta

Vyacheslav Egorov

Florian Schneider

Kevin Scott Millikin

Gautham Thambidorai

A programming model provides a method for type inference in programming operations. Information defining one or more attributes of an operation is received, the information specifying a field including a field name and a field type identifier for each of the attributes. Constraints for the operation are determined at least based on the attributes, wherein the constraints restrict at least one of a type of input for the operation or a type of output for the operation. Information defining an input for the operation is received, and it is determined, based on the constraints and the received information defining the input, the type of output for the operation. The type of output is associated with an output for the operation.

System of type inference for tuple graph programs

A programming model provides a method for executing a program in a distributed architecture. One or more first shards of the distributed architecture execute one or more operations, and sending tuples to at least one second shard, the tuples being part of a stream and being based on the one or more operations. The one or more first shards send a token value to the at least one second shard when the sending of the tuples in the stream is complete. The at least one second shard determines whether a total of the token values matches a number of the one or more first shards, and takes a first action in response to determining that the total of the token values matches the number of the one or more first shards. The first action may include marking the stream as being complete and/or generating a message indicating that the stream is complete.

Method of executing a tuple graph program across a network

System of type inference for tuple graph programs method of executing a tuple graph program across a network

A programming model generates a graph for a program, the graph including a plurality of nodes and edges, wherein each node of the graph represents an operation and edges between the nodes represent streams of data input to and output from the operations represented by the nodes. The model determines where in a distributed architecture to execute the operations represented by the nodes. Such determining may include determining which nodes have location restrictions, assigning locations to each node having a location restriction based on the restriction, and partitioning the graph into a plurality of subgraphs, the partitioning including assigning locations to nodes without location restrictions in accordance with a first set of constraints, wherein each node within a particular subgraph is assigned to the same location. Each of the subgraphs is executed at its assigned location in a respective single thread.

Method for intra-subgraph optimization in tuple graph programs

Aspects of the subject technology relate to a computer-implemented process, including steps for compiling a first method call at a first call site in code of an object-oriented language, wherein the first call site is associated with a first selector, referencing a global cache comprising a plurality of per-selector caches, wherein each of the per-selector caches is indexed based on a corresponding selector identification and identifying a first per-selector cache, from among the plurality of per-selector caches, using the first selector. In certain aspects, the process can further include steps for invoking a method on a first object by performing a lookup in the first per-selector cache using a class associated with the first object to determine if a first target function exists in the first per-selector cache. Systems and computer readable media are also provided.

Per-selector dispatch

Executing a set one or more instructions is disclosed. A set of one or more register states is saved in a software data structure. The set of instructions is speculatively executed. At least one store made to a memory location during the speculative execution is not committed until the speculative execution is successfully completed. If an abort indication is received, the state of one or more registers restored.

Concurrent atomic execution

Interacting with an external environment of a segmented virtual machine is disclosed. An indication that a communication with an external environment is desired is received. It is determined whether the communication can be initiated directly from a core virtual machine of the segmented virtual machine without initiating the communication from a shell virtual machine of the segmented virtual machine. An attempt to initiate the communication is made based as at least in part on the determination.

External data source redirection in segmented virtual machine

Detecting a race condition is disclosed. An indication of a store operation to a memory address is received. An identifier of the memory address is stored. The identifier is used to detect an occurrence of a memory operation that is not associated with a previous ordering operation.

Detecting software race conditions

Executing a set one or more instructions atomically is disclosed. Executing includes saving a set of one or more register states in a software data structure, speculatively executing the set of instructions, and restoring the state of one or more registers when an abort indication is received.

Executing a set of one or more instructions atomically is disclosed. Executing includes determining whether speculatively executing the instructions is advised based at least in part on dynamic information associated with synchronization data and speculatively executing the instructions when it is determined that speculatively executing the instructions is advised.

Dynamic concurrent atomic execution

Improving performance of a computer program is disclosed. A first set of escape data is gathered. A first compiled program is provided using the first set of escape data. A second set of escape data is gathered based on the first compiled program. A second compiled program is provided using the second set of escape data. The second compiled program is more optimized than the first compiled program.

Memory management

A technique for managing an object in memory is disclosed. The technique comprises: assigning the object to an assigned frame wherein the object can be released when the assigned frame is released; detecting an attempt to place a reference to the object in an older frame, the older frame being older than the assigned frame; and reassigning the object to a reassignment frame that is at least as old as the older frame.

Growing community of inventors

Menlo Park, CA, United States of America

Ivan Posva