Advanced Micro Devices Corporation

Blake A Hechtman

Bradford Michael Beckmann

Derek R Hower

Mark Donald Hill

Steven Karl Reinhardt

David Allen Wood

Benedict R Gaster

Shuai Che

A method, computer program product, and system is described that enforces a release consistency with special accesses sequentially consistent (RCsc) memory model and executes release synchronization instructions such as a StRel event without tracking an outstanding store event through a memory hierarchy, while efficiently using bandwidth resources. What is also described is the decoupling of a store event from an ordering of the store event with respect to a RCsc memory model. The description also includes a set of hierarchical read/write combining buffers that coalesce stores from different parts of the system. In addition, a pool component maintains partial order of received store events and release synchronization events to avoid content addressable memory (CAM) structures, full cache flushes, as well as direct write-throughs to memory. The approach improves the performance of both global and local synchronization events since a store event may not need to reach main memory to complete.

Write combining cache microarchitecture for synchronization events

Central processing units (CPUs) in computing systems manage graphics processing units (GPUs), network processors, security co-processors, and other data heavy devices as buffered peripherals using device drivers. Unfortunately, as a result of large and latency-sensitive data transfers between CPUs and these external devices, and memory partitioned into kernel-access and user-access spaces, these schemes to manage peripherals may introduce latency and memory use inefficiencies. Proposed are schemes to reduce latency and redundant memory copies using virtual to physical page remapping while maintaining user/kernel level access abstractions.

Mechanisms to save user/kernel copy for cross device communications

Sharing tasks among compute units in a processor can increase the efficiency of the processor. When a compute unit does not have a task in its task memory to perform, donating tasks from other compute units can prevent the compute unit from being idle while there is task in other parts of the processor. It is desirable to share tasks among compute units that are within defined scopes of the processor. Compute units may share tasks by allowing other compute units to access their private memory, or by donating tasks to a shared memory.

Runtime for automatically load-balancing and synchronizing heterogeneous computer systems with scoped synchronization

A method, computer program product, and system is described that enforces a release consistency with special accesses sequentially consistent (RCsc) memory model and executes release synchronization instructions such as a StRel event without tracking an outstanding store event through a memory hierarchy, while efficiently using bandwidth resources. What is also described is the decoupling of a store event from an ordering of the store event with respect to a RCsc memory model. The description also includes a set of hierarchical read-only cache and write-only combining buffers that coalesce stores from different parts of the system. In addition, a pool component maintains partial order of received store events and release synchronization events to avoid content addressable memory (CAM) structures, full cache flushes, as well as direct write-throughs to memory. The approach improves the performance of both global and local synchronization events and reduces overhead in maintaining write-only combining buffers.

Hierarchical write-combining cache coherence

A method, computer program product, and system is described that determines the correctness of using memory operations in a computing device with heterogeneous computer components. Embodiments include an optimizer based on the characteristics of a Sequential Consistency for Heterogeneous-Race-Free (SC for HRF) model that analyzes a program and determines the correctness of the ordering of events in the program. HRF models include combinations of the properties: scope order, scope inclusion, and scope transitivity. The optimizer can determine when a program is heterogeneous-race-free in accordance with an SC for HRF memory consistency model. For example, the optimizer can analyze a portion of program code, respect the properties of the SC for HRF model, and determine whether a value produced by a store memory event will be a candidate for a value observed by a load memory event. In addition, the optimizer can determine whether reordering of events is possible.

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Durham, NC, United States of America

Blake A Hechtman