Micron Technology Incorporated

Skyler Arron Windh

Patrick Alan Estep

Tony M Brewer

Allan Kennedy Porterfield

Gongyu Wang

Bashar Romanous

Randall Paul Meyer

Bryan D Hornung

Douglas John Vanesko

Devices and techniques for thread scheduling control and memory splitting in a processor are described herein. An apparatus includes a hardware interface configured to receive a first request to execute a first thread, the first request including an indication of a workload; and processing circuitry configured to: determine the workload to produce a metric based at least in part on the indication; compare the metric with a threshold to determine that the metric is beyond the threshold; divide, based at least in part on the comparison, the workload into a set of sub-workloads consisting of predefined number of equal parts from the workload; create a second request to execute a second thread, the second request including a first member of the set of sub-workloads; and process a second member of the set of sub-workloads in the first thread.

Dynamic decomposition and thread allocation

Schedule instructions of a program for execution on a coarse grained reconfigurable array having a plurality of tiles operable in parallel. The program identifies data flows through memory locations represented by memory variables and identifies instructions configured to transform data in the data flows. Based on a hardware profile identifying features of the coarse grained reconfigurable array, a scheduler is configured to generate a memory map. The memory map identifies, for each respective memory variable in the program, one of the tiles that contains a memory location represented by the respective memory variable. Based on the memory map reducing possible choices for a brute force search, the scheduler assigns the instructions to the tiles for execution, and determines timing of execution of the instructions in the tiles.

Schedule instructions of a program of data flows for execution in tiles of a coarse grained reconfigurable array

Disclosed in some examples, are systems, methods, devices, and machine readable mediums which use improved dynamic programming algorithms to pack conditional branch instructions. Conditional code branches may be modeled as directed acyclic graphs (DAGs) which have a topological ordering. These DAGs may be used to construct a dynamic programming table to find a partial mapping of one path onto the other path using dynamic programming algorithms.

Packing conditional branch operations

An assembly language program for a coarse grained reconfiguration array (CGRA), having dispatch interface information indicating operations to be performed via a dispatch interface of the CGRA to receive an input, memory interface information indicating operations to be performed via one or more memory interfaces of the CGRA, tile memory information indicating memory variables referring to memory locations to be implemented in tile memories of the CGRA, a flow description specifying one or more synchronous data flows, through the memory locations referenced via the memory variables in the tile memory information, to produce a result from the input using the CGRA.

Programming a coarse grained reconfigurable array through description of data flow graphs

Devices and techniques for triggering early termination of cooperating processes in a processor are described herein. A system includes multiple memory-compute nodes, wherein a memory-compute node comprises: event manager circuitry configured to establish a broadcast channel to receive event messages; and thread manager circuitry configured to organize a plurality of threads to perform portions of a cooperative task, wherein the plurality of threads each monitor the broadcast channel to receive event messages on the broadcast channel, and wherein upon achieving a threshold operation, the thread manager circuitry is to use the event manager circuitry to broadcast, on the broadcast channel, an event message indicating that the cooperative task is complete, causing other threads, in response to receiving the event message, to terminate execution of their respective portions of the cooperative task.

Mechanism to trigger early termination of cooperating processes

A reconfigurable compute fabric can include multiple nodes, and each node can include multiple tiles with respective processing and storage elements. The tiles can be arranged in an array or grid and can be communicatively coupled. In an example, a first node can include a tile cluster of N memory-compute tiles, and the N memory-compute tiles can be coupled using a first portion of a synchronous compute fabric. Operations performed by the respective processing and storage elements of the N memory-compute tiles can be selectively enabled or disabled based on information in a mask field of data propagated through the first portion of the synchronous compute fabric.

Mask field propagation among memory-compute tiles in a reconfigurable architecture

Disclosed in some examples are methods, systems, devices, and machine-readable mediums that use parallel hardware execution with software co-simulation to enable more advanced debugging operations on data flow architectures. Upon a halt to execution of a program thread, a state of the tiles that are executing the thread are saved and offloaded from the HTF to a host system. A developer may then examine this state on the host system to debug their program. Additionally, the state may be loaded into a software simulator that simulates the HTF hardware. This simulator allows for the developer to step through the code and to examine values to find bugs.

Debugging dataflow computer architectures

Latency in a node-based compute-near-memory system can be problematic. A solution to the problem can include or use a dedicated software-based cache at each node. The cache can be configured to store information received from each of the other nodes in the system. In an example, the cache can be populated during a breadth first search algorithm to store frontier information from each of the other nodes.

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McKinney, TX, United States of America

Skyler Arron Windh