Scalable Non-Blocking Concurrent Objects for Mission Critical Code

Total Page:16

File Type:pdf, Size:1020Kb

Scalable Non-Blocking Concurrent Objects for Mission Critical Code Scalable Nonblocking Concurrent Objects for Mission Critical Code Damian Dechev Bjarne Stroustrup Texas A&M University, Texas A&M University, College Station, TX 77843-3112, U.S.A. College Station, TX 77843-3112, U.S.A. [email protected] [email protected] Abstract General Terms Algorithms, Languages, Reliability The high degree of complexity and autonomy of future robotic Keywords nonblocking synchronization, C++, ABA problem pre- space missions, such as Mars Science Laboratory (MSL), poses vention, software transactional memory, autonomous space soft- serious challenges in assuring their reliability and efficiency. Pro- ware viding fast and safe concurrent synchronization is of critical im- portance to such autonomous embedded software systems. The ap- plication of nonblocking synchronization is known to help elimi- 1. Introduction nate the hazards of deadlock, livelock, and priority inversion. The Robotic space mission projects, such as Mars Science Laboratory nonblocking programming techniques are notoriously difficult to (MSL) [29], pose the challenging task of engineering some of the implement and offer a variety of semantic guarantees and usabil- most complex real-time embedded software systems. The notion ity and performance trade-offs. The present software development of concurrency is of critical importance for the design and imple- and certification methodologies applied at NASA do not reach the mentation of such systems. The present software development and level of detail of providing guidelines for the design of concurrent certification protocols (such as [26]) do not reach the level of de- software. The complex task of engineering reliable and efficient tail of offering guidelines for the engineering of reliable concur- concurrent synchronization is left to the programmer’s ingenuity. rent software. In this work, we provide a detailed analysis of the A number of Software Transactional Memory (STM) approaches state-of-the-art nonblocking programming techniques and derive a gained wide popularity because of their easy to apply interfaces, generic implementation for scalable lightweight concurrent objects but currently fail to offer scalable nonblocking transactions. In this that can help in implementing efficient and safe concurrent interac- work we provide an in-depth analysis of the nonblocking syn- tions in mission critical code. chronization semantics and their applicability in mission critical code. We describe a generic implementation of a methodology for 1.1 Nonblocking Objects scalable implementation of concurrent objects. Our performance The most common technique for controlling the interactions of con- evaluation demonstrates that our approach is practical and outper- current processes is the use of mutual exclusion locks. A mutual forms the application of nonblocking transactions by a large fac- exclusion lock guarantees thread-safety of a concurrent object by tor. In addition, we apply our Descriptor-based approach to pro- blocking all contending threads trying to access it except the one vide a solution to the fundamental ABA problem. Our ABA pre- holding the lock. In scenarios of high contention on the shared data, vention scheme, called the λδ approach, outperforms by a large such an approach can seriously affect the performance of the sys- factor the use of garbage collection for the safe management of tem and significantly diminish its parallelism. For the majority of each shared location. It offers speeds comparable to the applica- applications, the problem with locks is one of difficulty of provid- tion of the architecture-specific CAS2 instruction used for version ing correctness more than one of performance. The application of counting. The λδ approach is an ABA prevention technique based mutual exclusion locks poses significant safety hazards and incurs on classification of concurrent operations and 3-step execution of high complexity in the testing and validation of mission-critical a Descriptor object. A practical alternative to the application of software. Locks can be optimized in some scenarios by utilizing CAS2 is particularly important for the engineering of embedded fine-grained locks or context-switching. Because of resource limi- systems. tations, optimized lock mechanisms are not a desirable alternative for flight-qualified hardware [24]. Even for efficient locks, the in- Categories and Subject Descriptors D.3.3 [Programming Lan- terdependence of processes implied by the use of mutual exclusion guages]: Language Constructs and Features introduces the dangers of deadlock, livelock, and priority inversion. The incorrect application of locks is hard to detect with the tradi- tional testing procedures and a program can be deployed and used for a long period of time before the flaws become evident and even- tually cause anomalous behavior. To achieve higher safety and gain performance, we suggest the Permission to make digital or hard copies of all or part of this work for personal or application of nonblocking synchronization. A concurrent object is classroom use is granted without fee provided that copies are not made or distributed nonblocking if it guarantees that some process in the system will for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute make progress in a finite amount of steps [16]. An object that guar- to lists, requires prior specific permission and/or a fee. antees that each process will make progress in a finite number of OOPSLA’09, October 25–29, 2009, Orlando, Florida, USA. steps is defined as wait-free. Obstruction-freedom [18] is an al- Copyright c 2009 ACM 978-1-60558-768-4/09/10. $10.00 ternative nonblocking condition that ensures progress if a thread eventually executes in isolation. It is the weakest nonblocking prop- part of the control system rather than a part of the system under erty and obstruction-free objects require the support of a contention control. There are dedicated state variables representing the data manager to prevent livelocking. states. In addition, data states can be controlled through the defi- nition of data goals. A data state might store information such as 1.2 Impact for Space Systems location, formatting, compression, and transport intent and status Modern robotic space exploration missions, such as Mars Science of the data. A data state might not be necessary for every state vari- Laboratory [29], are expected to embed a large array of advanced able. In a simple control system where no telemetry is used, the components and functionalities and perform a complex set of sci- state variable implementation might as well store the information entific experiments. The high degree of autonomy and increased regarding the variable’s value history and its extrapolated states. complexity of such systems pose significant challenges in assur- At its present state of design and implementation, MDS does not ing the reliability and efficiency of their software. A survey on the provide a concurrent synchronization mechanism for building safer challenges for the development of modern spacecraft software by and faster concurrent interactions. Elevating the level of efficiency Lowry [24] reveals that in July 1997 the Mars Pathfinder mission and reliability in the execution of the concurrent processes is of experienced a number of anomalous system resets that caused an particular significance to the implementation of the System Control operational delay and loss of scientific data. The follow-up analy- and the Data Management modules of MDS. It is the goal of this sis identified the presence of a priority inversion problem caused paper to illustrate the trade-offs in the semantics and application of by the low-priority meteorological process blocking the the high- some advanced nonblocking techniques and analyze their applica- priority bus management process. The software engineers found bility in MDS. The most ubiquitous and versatile data structure in out that it would have been impossible to detect the problem with the ISO C++ Standard Template Library (STL) [28] is vector, offer- the black box testing applied at the time. A more appropriate pri- ing a combination of dynamic memory management and constant- ority inversion inheritance algorithm had been ignored due to its time random access. Because of the vector’s wide use and chal- frequency of execution, the real-time requirements imposed, and lenging parallel implementation of its nonblocking dynamic oper- its high cost incurred on the slower flight-qualified computer hard- ations, we illustrate the efficiency of each nonblocking approach ware. The subtle interactions in the concurrent applications of the discussed in this work with respect to its applicability for the de- modern aerospace autonomous software are of critical importance sign and implementation of a shared nonblocking vector. A number to the system’s safety and operation. The presence of a large num- of pivotal concurrent applications in the Mission Data System [20] ber of concurrent autonomous processes implies an increased vol- framework employ a shared STL vector (in all scenarios protected ume of interactions that are hard to predict and validate. Allowing by mutual exclusion locks). Such is the Data Management Service fast and reliable concurrent synchronization is of critical impor- library described by Wagner in [30]. tance to the design of autonomous spacecraft software. 2. Nonblocking Data Structures 1.3 Mission Data System Lock-free
Recommended publications
  • The Challenges of Hardware Synthesis from C-Like Languages
    The Challenges of Hardware Synthesis from C-like Languages Stephen A. Edwards∗ Department of Computer Science Columbia University, New York Abstract most successful C-like languages, in fact, bear little syntactic or semantic resemblance to C, effectively forcing users to learn The relentless increase in the complexity of integrated circuits a new language anyway. As a result, techniques for synthesiz- we can fabricate imposes a continuing need for ways to de- ing hardware from C either generate inefficient hardware or scribe complex hardware succinctly. Because of their ubiquity propose a language that merely adopts part of C syntax. and flexibility, many have proposed to use the C and C++ lan- For space reasons, this paper is focused purely on the use of guages as specification languages for digital hardware. Yet, C-like languages for synthesis. I deliberately omit discussion tools based on this idea have seen little commercial interest. of other important uses of a design language, such as validation In this paper, I argue that C/C++ is a poor choice for specify- and algorithm exploration. C-like languages are much more ing hardware for synthesis and suggest a set of criteria that the compelling for these tasks, and one in particular (SystemC) is next successful hardware description language should have. now widely used, as are many ad hoc variants. 1 Introduction 2 A Short History of C Familiarity is the main reason C-like languages have been pro- Dennis Ritchie developed C in the early 1970 [18] based on posed for hardware synthesis. Synthesize hardware from C, experience with Ken Thompson’s B language, which had itself proponents claim, and we will effectively turn every C pro- evolved from Martin Richards’ BCPL [17].
    [Show full text]
  • Synchronously Waiting on Asynchronous Operations
    Document No. P1171R0 Date 2018-10-07 Reply To Lewis Baker <[email protected]> Audience SG1, LEWG Synchronously waiting on asynchronous operations Overview The paper P1056R0 introduces a new std::experimental::task<T> type. This type represents an ​ ​ ​ ​ ​ asynchronous operation that requires applying operator co_await to the task retrieve the result. The task<T> ​ type is an instance of the more general concept of Awaitable types. The limitation of Awaitable types is that they can only be co_awaited from within a coroutine. For example, from the body of another task<T> coroutine. However, then you still end up with another Awaitable type that must be co_awaited within another coroutine. This presents a problem of how to start executing the first task and wait for it to complete. task<int> f(); task<int> g() { // Call to f() returns a not-yet-started task. // Applying operator co_await() to the task starts its execution // and suspends the current coroutine until it completes. int a = co_await f(); co_return a + 1; } int main() { task<int> t = g(); // But how do we start executing g() and waiting for it to complete // when outside of a coroutine context, such as in main()? int x = ???; return x; } This paper proposes a new function, sync_wait(), that will allow a caller to pass an arbitrary Awaitable type ​ ​ into the function. The function will co_await the passed Awaitable object on the current thread and then block ​ ​ waiting for that co_await operation to complete; either synchronously on the current thread, or ​ ​ asynchronously on another thread. When the operation completes, the result is captured on whichever thread the operation completed on.
    [Show full text]
  • Lock-Free Programming
    Lock-Free Programming Geoff Langdale L31_Lockfree 1 Desynchronization ● This is an interesting topic ● This will (may?) become even more relevant with near ubiquitous multi-processing ● Still: please don’t rewrite any Project 3s! L31_Lockfree 2 Synchronization ● We received notification via the web form that one group has passed the P3/P4 test suite. Congratulations! ● We will be releasing a version of the fork-wait bomb which doesn't make as many assumptions about task id's. – Please look for it today and let us know right away if it causes any trouble for you. ● Personal and group disk quotas have been grown in order to reduce the number of people running out over the weekend – if you try hard enough you'll still be able to do it. L31_Lockfree 3 Outline ● Problems with locking ● Definition of Lock-free programming ● Examples of Lock-free programming ● Linux OS uses of Lock-free data structures ● Miscellanea (higher-level constructs, ‘wait-freedom’) ● Conclusion L31_Lockfree 4 Problems with Locking ● This list is more or less contentious, not equally relevant to all locking situations: – Deadlock – Priority Inversion – Convoying – “Async-signal-safety” – Kill-tolerant availability – Pre-emption tolerance – Overall performance L31_Lockfree 5 Problems with Locking 2 ● Deadlock – Processes that cannot proceed because they are waiting for resources that are held by processes that are waiting for… ● Priority inversion – Low-priority processes hold a lock required by a higher- priority process – Priority inheritance a possible solution L31_Lockfree
    [Show full text]
  • CMS Application Multitasking
    z/VM Version 7 Release 1 CMS Application Multitasking IBM SC24-6258-00 Note: Before you use this information and the product it supports, read the information in “Notices” on page 337. This edition applies to version 7, release 1, modification 0 of IBM® z/VM® (product number 5741-A09) and to all subsequent releases and modifications until otherwise indicated in new editions. Last updated: 2018-09-12 © Copyright International Business Machines Corporation 1992, 2018. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents List of Figures....................................................................................................... ix List of Tables........................................................................................................ xi About This Document..........................................................................................xiii Intended Audience.................................................................................................................................... xiii Where to Find More Information...............................................................................................................xiii Links to Other Documents and Websites............................................................................................ xiii How to Send Your Comments to IBM.....................................................................xv Summary of Changes for z/VM CMS Application Multitasking..............................
    [Show full text]
  • Automating Non-Blocking Synchronization in Concurrent Data Abstractions
    Automating Non-Blocking Synchronization In Concurrent Data Abstractions Jiange Zhang Qing Yi Damian Dechev University of Colorado at University of Colorado at University of Central Florida Colorado Springs, CO, USA Colorado Springs, CO, USA Orlando, FL, USA [email protected] [email protected] [email protected] Abstract—This paper investigates using compiler tion needs. We show that by automatically weaving syn- technology to automatically convert sequential C++ chronization schemes with sequential implementations of data abstractions, e.g., queues, stacks, maps, and trees, data structures, many efficient lock-free data structures to concurrent lock-free implementations. By auto- matically tailoring a number of state-of-the-practice can be made readily available, with performance compet- synchronization methods to the underlying sequen- itive to that of the manually crafted ones by experts. tial implementations of different data structures, our The key technical difference between our work and exist- automatically synchronized code can attain perfor- ing STM research is that we support multiple synchroniza- mance competitive to that of concurrent data struc- tion strategies and automatically select the best strategy tures manually-written by experts and much better performance than heavier-weight support by software for each piece of code at compile time. No existing compiler transactional memory (STM). for STM supports automatic tailoring of synchronizations to what is needed by different pieces of code. The compiler I. Introduction algorithms we present are the first to do this. While we The advent of the multi-core era has brought multi- mostly rely on standard compiler techniques (e.g., pointer threaded programming to the mainstream and with it the and data-flow analysis), the problem formulations and challenges of managing shared data among the threads.
    [Show full text]
  • Mutual Exclusion: Classical Algorithms for Locks
    Mutual Exclusion: Classical Algorithms for Locks Bill Scherer Department of Computer Science Rice University [email protected] COMP 422 Lecture 20 March 2008 Motivation Ensure that a block of code manipulating a data structure is executed by only one thread at a time • Why? avoid conflicting accesses to shared data (data races) —read/write conflicts —write/write conflicts • Approach: critical section • Mechanism: lock —methods – acquire – release • Usage —acquire lock to enter the critical section —release lock to leave the critical section 2 Problems with Locks • Conceptual —coarse-grained: poor scalability —fine-grained: hard to write • Semantic —deadlock —priority inversion • Performance —convoying —intolerance of page faults and preemption 3 Lock Alternatives • Transactional memory (TM) + Easy to use, well-understood metaphor – High overhead (so far) ± Subject of much active research • Ad hoc nonblocking synchronization (NBS) + Thread failure/delay cannot prevent progress + Can be faster than locks (stacks, queues) – Notoriously difficult to write – every new algorithm is a publishable result + Can be “canned” in libraries (e.g. java.util) 4 Synchronization Landscape Ad Hoc NBS Fine Locks Software HW TM (STM) TM Programmer Effort Coarse Canned Locks NBS System Performance 5 Properties of Good Lock Algorithms • Mutual exclusion (safety property) —critical sections of different threads do not overlap – cannot guarantee integrity of computation without this property • No deadlock —if some thread attempts to acquire the lock, then some
    [Show full text]
  • Synchronization Key Concepts: Critical Sections, Mutual Exclusion, Test-And-Set, Spinlocks, Blocking and Blocking Locks, Semaphores, Condition Variables, Deadlocks
    Synchronization key concepts: critical sections, mutual exclusion, test-and-set, spinlocks, blocking and blocking locks, semaphores, condition variables, deadlocks Ali Mashtizadeh and Lesley Istead David R. Cheriton School of Computer Science University of Waterloo Fall 2019 1 / 56 Thread Synchronization All threads in a concurrent program share access to the program's global variables and the heap. The part of a concurrent program in which a shared object is accessed is called a critical section. What happens if several threads try to access the same global variable or heap object at the same time? 2 / 56 Critical Section Example /* Note the use of volatile; revisit later */ int ________volatiletotal = 0; void add() f void sub() f int i; int i; for (i=0; i<N; i++) f for (i=0; i<N; i++) f total++; total--; g g g g If one thread executes add and another executes sub what is the value of total when they have finished? 3 / 56 Critical Section Example (assembly detail) /* Note the use of volatile */ int ________volatiletotal = 0; void add() f void sub() f loadaddr R8 total loadaddr R10 total for (i=0; i<N; i++) f for (i=0; i<N; i++) f lw R9 0(R8) lw R11 0(R10) add R9 1 sub R11 1 sw R9 0(R8) sw R11 0(R10) g g g g 4 / 56 Critical Section Example (Trace 1) Thread 1 Thread 2 loadaddr R8 total lw R9 0(R8) R9=0 add R9 1 R9=1 sw R9 0(R8) total=1 <INTERRUPT> loadaddr R10 total lw R11 0(R10) R11=1 sub R11 1 R11=0 sw R11 0(R10) total=0 One possible order of execution.
    [Show full text]
  • Concurrent Programming Without Locks
    Concurrent Programming Without Locks KEIR FRASER University of Cambridge Computer Laboratory and TIM HARRIS Microsoft Research Cambridge Mutual exclusion locks remain the de facto mechanism for concurrency control on shared-memory data structures. However, their apparent simplicity is deceptive: it is hard to design scalable locking strategies because locks can harbour problems such as priority inversion, deadlock and convoying. Furthermore, scalable lock-based systems are not readily composable when building compound operations. In looking for solutions to these problems, interest has developed in non- blocking systems which have promised scalability and robustness by eschewing mutual exclusion while still ensuring safety. However, existing techniques for building non-blocking systems are rarely suitable for practical use, imposing substantial storage overheads, serialising non-conflicting operations, or requiring instructions not readily available on today’s CPUs. In this paper we present three APIs which make it easier to develop non-blocking implemen- tations of arbitrary data structures. The first API is a multi-word compare-and-swap operation (MCAS) which atomically updates a set of memory locations. This can be used to advance a data structure from one consistent state to another. The second API is a word-based software transactional memory (WSTM) which can allow sequential code to be re-used more directly than with MCAS and which provides better scalability when locations are being read rather than being updated. The third API is an object-based software transactional memory (OSTM). OSTM allows a more streamlined implementation than WSTM, but at the cost of re-engineering the code to use OSTM objects. We present practical implementations of all three of these APIs, built from operations available across all of today’s major CPU families.
    [Show full text]
  • Enabling Task Level Parallelism in Handelc Thamer S
    Enabling Task Level Parallelism in HandelC Thamer S. AbuYasin Submitted to the Department of Electrical Engineering & Computer Science and the Faculty of the Graduate School of the University of Kansas in partial fulfillment of the requirements for the degree of Master’s of Science Thesis Committee: Dr. David Andrews: Chairperson Dr. Arvin Agah Dr. Perry Alexander Date Defended 2007/12/14 The Thesis Committee for Thamer S. AbuYasin certifies That this is the approved version of the following thesis: Enabling Task Level Parallelism in HandelC Committee: Chairperson Date Approved i Chapter 1 Abstract HandelC is a programming language used to target hardware and is similar in syntax to ANSI-C. HandelC offers constructs that allow programmers to express instruction level parallelism. Also, HandelC offers primitives that allow task level parallelism. However, HandelC does not offer any runtime support that enables programmers to express task level parallelism efficiently. This thesis discusses this issue and suggests a support library called HCthreads as a solution. HCthreads offers a subset of Pthreads functionality and interface relevant to the HandelC environment. This study offers means to identify the best configuration of HC- threads to achieve the highest speedups in real systems. This thesis investigates the issue of integrating HandelC within platforms not supported by Celoxica. A support library is implemented to solve this issue by utilizing the high level abstractions offered by Hthreads. This support library abstracts away any HWTI specific synchronization making the coding experience quite close to software. HCthreads is proven effective and generic for various algorithms with different threading behaviors. HCthreads is an adequate method to implement recursive algorithms even if no task level parallelism is warranted.
    [Show full text]
  • Concurrent Data Structures
    1 Concurrent Data Structures 1.1 Designing Concurrent Data Structures ::::::::::::: 1-1 Performance ² Blocking Techniques ² Nonblocking Techniques ² Complexity Measures ² Correctness ² Verification Techniques ² Tools of the Trade 1.2 Shared Counters and Fetch-and-Á Structures ::::: 1-12 1.3 Stacks and Queues :::::::::::::::::::::::::::::::::::: 1-14 1.4 Pools :::::::::::::::::::::::::::::::::::::::::::::::::::: 1-17 1.5 Linked Lists :::::::::::::::::::::::::::::::::::::::::::: 1-18 1.6 Hash Tables :::::::::::::::::::::::::::::::::::::::::::: 1-19 1.7 Search Trees:::::::::::::::::::::::::::::::::::::::::::: 1-20 Mark Moir and Nir Shavit 1.8 Priority Queues :::::::::::::::::::::::::::::::::::::::: 1-22 Sun Microsystems Laboratories 1.9 Summary ::::::::::::::::::::::::::::::::::::::::::::::: 1-23 The proliferation of commercial shared-memory multiprocessor machines has brought about significant changes in the art of concurrent programming. Given current trends towards low- cost chip multithreading (CMT), such machines are bound to become ever more widespread. Shared-memory multiprocessors are systems that concurrently execute multiple threads of computation which communicate and synchronize through data structures in shared memory. The efficiency of these data structures is crucial to performance, yet designing effective data structures for multiprocessor machines is an art currently mastered by few. By most accounts, concurrent data structures are far more difficult to design than sequential ones because threads executing concurrently may interleave
    [Show full text]
  • UNIT 10C Multitasking & Operating Systems
    11/5/2011 UNIT 10C Concurrency: Multitasking & Deadlock 15110 Principles of Computing, Carnegie 1 Mellon University - CORTINA Multitasking & Operating Systems • Multitasking - The coordination of several computational processes on one processor. • An operating system (OS) is the system software responsible for the direct control and management of hardware and basic system operations. • An OS provides a foundation upon which to run application software such as word processing programs, web browsers, etc. from Wikipedia 15110 Principles of Computing, Carnegie 2 Mellon University - CORTINA 1 11/5/2011 Operating System “Flavors” • UNIX – System V, BSD, Linux – Proprietary: Solaris, Mac OS X • Windows – Windows XP – Windows Vista – Windows 7 15110 Principles of Computing, Carnegie 3 Mellon University - CORTINA Multitasking • Each (un-blocked) application runs for a very short time on the computer's processor and then another process runs, then another... • This is done at such a fast rate that it appears to the computer user that all applications are running at the same time. – How do actors appear to move in a motion picture? 15110 Principles of Computing, Carnegie 4 Mellon University - CORTINA 2 11/5/2011 Critical Section • A critical section is a section of computer code that must only be executed by one process or thread at a time. • Examples: – A printer queue receiving a file to be printed – Code to set a seat as reserved – Web server that generates and returns a web page showing current registration in course 15110 Principles of Computing, Carnegie 5 Mellon University - CORTINA A Critical Section Cars may not make turns through this intersection. They may only proceed straight ahead.
    [Show full text]
  • Deadlocks (Chapter 3, Tanenbaum)
    Deadlocks (Chapter 3, Tanenbaum) Copyright © 1996±2002 Eskicioglu and Marsland (and Prentice-Hall and July 99 Paul Lu) Deadlocks What is a deadlock? Deadlock is defined as the permanent blocking of a set of processes that compete for system resources, including database records or communication lines. Unlike other problems in multiprogramming systems, there is no efficient solution to the deadlock problem in the general case. Deadlock prevention, by design, is the ªbestº solution. Deadlock occurs when a set of processes are in a wait state, because each process is waiting for a resource that is held by some other waiting process. Therefore, all deadlocks involve conflicting resource needs by two or more processes. Copyright © 1996±2002 Eskicioglu and Marsland (and Prentice-Hall and July 99 Paul Lu) Deadlocks 2 Classification of resourcesÐI Two general categories of resources can be distinguished: · Reusable: something that can be safely used by one process at a time and is not depleted by that use. Processes obtain resources that they later release for reuse by others. E.g., CPU, memory, specific I/O devices, or files. · Consumable: these can be created and destroyed. When a resource is acquired by a process, the resource ceases to exist. E.g., interrupts, signals, or messages. Copyright © 1996±2002 Eskicioglu and Marsland (and Prentice-Hall and July 99 Paul Lu) Deadlocks 3 Classification of resourcesÐII One other taxonomy again identifies two types of resources: · Preemptable: these can be taken away from the process owning it with no ill effects (needs save/restore). E.g., memory or CPU. · Non-preemptable: cannot be taken away from its current owner without causing the computation to fail.
    [Show full text]