Deferral instruction for managing transactional aborts in transactional memory computing environments

#This disclosure relates generally to transaction processing in a multi-processor computing environment with transactional memory, and more specifically to using a deferral instruction for managing transactional aborts in a transactional memory computing environment.

#The number of central processing unit (CPU) cores on a chip and the number of CPU cores connected to a shared memory continue to grow significantly to support growing workload capacity demand. The increasing number of CPUs cooperating to process the same workloads puts a significant burden on software scalability; for example, shared queues or data-structures protected by traditional semaphores become hot spots and lead to sub-linear n-way scaling curves. Traditionally this has been countered by implementing finer-grained locking in software, and with lower latency/higher bandwidth interconnects in hardware. Implementing fine-grained locking to improve software scalability can be very complicated and error-prone, and at today's CPU frequencies, the latencies of hardware interconnects are limited by the physical dimension of the chips and systems, and by the speed of light.

#Implementations of hardware Transactional Memory (HTM, or in this discussion, simply TM) have been introduced, wherein a group of instructions—called a transaction—operate in an atomic manner on a data structure in memory, as viewed by other central processing units (CPUs) and the I/O subsystem (atomic operation is also known as “block concurrent” or “serialized” in other literature). The transaction executes optimistically without obtaining a lock, but may need to abort and retry the transaction execution if an operation of the executing transaction on a memory location conflicts with another operation on the same memory location. Previously, software transactional memory implementations have been proposed to support software Transactional Memory (TM). However, hardware TM can provide improved performance aspects and ease of use over software TM.

#One or more aspects of the present disclosed embodiments are particularly pointed out and distinctly claimed as examples in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the disclosed embodiments are apparent from the following detailed description taken in conjunction with the accompanying drawings in which:

#FIG. 1 depicts an example multicore Transactional Memory environment, in accordance with embodiments of the present disclosure;

#FIG. 2 depicts example components of an example CPU, in accordance with embodiments of the present disclosure;

#Historically, a computer system or processor had only a single processor (also known as processing unit or central processing unit). The processor included an instruction processing unit (IPU), a branch unit, a memory control unit and the like. Such processors were capable of executing a single thread of a program at a time. Operating systems were developed that could time-share a processor by dispatching a program to be executed on the processor for a period of time, and then dispatching another program to be executed on the processor for another period of time. As technology evolved, memory subsystem caches were often added to the processor as well as complex dynamic address translation including translation lookaside buffers (TLBs). The IPU itself was often referred to as a processor. As technology continued to evolve, an entire processor could be packaged in a single semiconductor chip or die; such a processor was referred to as a microprocessor. Then processors were developed that incorporated multiple IPUs; such processors were often referred to as multi-processors. Each such processor of a multi-processor computer system (processor) may include individual or shared caches, memory interfaces, system bus, address translation mechanism and the like. Virtual machine and instruction set architecture (ISA) emulators added a layer of software to a processor that provided the virtual machine with multiple “virtual processors” (also known as processors) by time-slice usage of a single IPU in a single hardware processor. As technology further evolved, multi-threaded processors were developed, enabling a single hardware processor having a single multi-thread IPU to provide a capability of simultaneously executing threads of different programs, thus each thread of a multi-threaded processor appeared to the operating system as a processor. As technology further evolved, it was possible to put multiple processors (each having an IPU) on a single semiconductor chip or die. These processors were referred to processor cores or just cores. Thus the terms such as processor, central processing unit, processing unit, microprocessor, core, processor core, processor thread, and thread, for example, are often used interchangeably. Aspects of embodiments herein may be practiced by any or all processors including those shown supra, without departing from the teachings herein. Wherein the term “thread” or “processor thread” is used herein, it is expected that particular advantage of the embodiment may be had in a processor thread implementation.

#Transaction Execution in Intel® Based Embodiments

#In “Intel® Architecture Instruction Set Extensions Programming Reference” 319433-012A, February 2012, incorporated herein by reference in its entirety, Chapter 8 teaches, in part, that multithreaded applications may take advantage of increasing numbers of CPU cores to achieve higher performance. However, the writing of multi-threaded applications requires programmers to understand and take into account data sharing among the multiple threads. Access to shared data typically requires synchronization mechanisms. These synchronization mechanisms are used to ensure that multiple threads update shared data by serializing operations that are applied to the shared data, often through the use of a critical section that is protected by a lock. Since serialization limits concurrency, programmers try to limit the overhead due to synchronization.