We present a new technique, Safe Concurrent Optimistic Traversals (SCOT), to address a well-known problem related to optimistic traversals with classical and more recent safe memory reclamation (SMR) schemes, such as Hazard Pointers (HP), Hazard Eras (HE), Interval-Based Reclamation (IBR), and Hyaline. Unlike Epoch-Based Reclamation (EBR), these (robust) schemes protect against stalled threads but lack support for well-known data structures with optimistic traversals, e.g., Harris' list and the Natarajan-Mittal tree. Such schemes are either incompatible with them or need changes with performance trade-offs (e.g., the Harris-Michael list).

We present two system services - the storage service and the file system service designed for private cloud environments to facilitate file sharing across different virtual machines (VMs). Our services are scalable, fault-tolerant, and deliver excellent performance. These system servers are implemented as unikernels running atop of the Xen hypervisor. Additionally, our storage service can leverage NetBSD code, enabling support for a wide range of both legacy and modern storage devices, such as NVMe. Furthermore, the storage service addresses the challenge of transparent fault recovery for storage, a complex task for stateful subsystems, without incurring significant overhead - a well-known challenge in storage systems. Our file system service is designed to be copy-free, enhancing overall performance. We have also designed an inter-VM communication (IVMC) mechanism that fosters scalability and reliability by leveraging lock-free concurrent ring buffers. Since this mechanism is lock-free, our system services communicate with application VMs in a more scalable manner compared to traditional ring buffers used in hypervisors such as Xen. Our lock-free design also aids in restoring storage states during the fault recovery process of the storage server. Our evaluation results demonstrate that our system services achieve performance comparable to that of Linux.

We present Safe Concurrent Optimistic Traversals (SCOT), to address a well-known problem related to optimistic traversals with both classical and more recent memory reclamation schemes, such as Hazard Pointers (HP), Hazard Eras (HE), Interval-Based Reclamation (IBR), and Hyaline. For these schemes, unlike for Epoch-Based Reclamation (EBR), existing data structure implementations are either buggy (e.g., Natarajan-Mittal tree) or come with performance trade-offs (e.g., Harris-Michael modified list).

Traditionally, most concurrent algorithms rely on safe memory reclamation (SMR)schemes for manual memory management. SMR schemes such as epoch-based reclamation (EBR) and hazard pointers (HP) are typically viewed as the only solution for memory recycling. When using SMR, a new object needs to be allocated whenever something new is added to a data structure. However, in more complex scenarios, the same object may need to be moved between different data structures (e.g., moving a node from one list to another, and then back to the original list) in a copy-free manner, i.e., without deallocating and allocating the node again. It is typically impossible for two reasons: (1) the ABA problem would still arise even when using SMR since the same pointer can reappear (without going through the full SMR cycle) if the same node eventually ends up back in the original data structure; (2) while in simple queues and stacks, nodes can immediately be recycled, it is unclear how to adapt data structures which use non-trivial traversal and two-phase deletion strategies, e.g., linked lists, skip lists, hash tables, trees, etc., where it is seemingly impossible to always immediately move (logically) deleted objects since they might still be accessed by other threads. We propose a general method of creating RRR (Reduce, Reuse, Recycle) data structures to allow safe memory recycling when using SMR which addresses the above-mentioned problems. Our method is applicable to linked lists, skip lists, hash tables, Natarajan-Mittal tree, and other data structures. We also discuss and propose a specialized approach – a more efficient version of Michael-and-Scott’s (recycling) queue. Our evaluation on x86-64 shows promising results when using our methods for different data structures and SMR schemes.

Historically, memory management based on lock-free reference counting was very inefficient, especially for read-dominated workloads. Thus, approaches such as epoch-based reclamation (EBR), hazard pointers (HP), or a combination thereof have received significant attention. EBR exhibits excellent performance but is blocking due to potentially unbounded memory usage. In contrast, HP are non-blocking and achieve good memory efficiency but are much slower. Moreover, HP are only lock-free in the general case. Recently, several new memory reclamation approaches such as WFE and Hyaline have been proposed. WFE achieves wait-freedom, but is less memory efficient and performs suboptimally in oversubscribed scenarios; Hyaline achieves higher performance and memory efficiency, but lacks wait-freedom. We present a family of non-blocking memory reclamation schemes, called Crystalline, that simultaneously addresses the challenges of high performance, high memory efficiency, and wait-freedom. Crystalline can guarantee complete wait-freedom even when threads are dynamically recycled, asynchronously reclaims memory in the sense that any thread can reclaim memory retired by any other thread, and ensures (an almost) balanced reclamation workload across all threads. The latter two properties result in Crystalline’s high performance and memory efficiency. Simultaneously ensuring all three properties requires overcoming unique challenges. Crystalline supports ubiquitous x86-64 and ARM64 architectures, while achieving superior throughput than prior fast schemes such as EBR as the number of threads grows. We also accentuate that many recent approaches, unlike HP, lack strict non-blocking guarantees when used with multiple data structures. By providing full wait-freedom, Crystalline addresses this problem as well.

While address space layout randomization (ASLR) has been extensively studied for user-space programs, the corresponding OS kernel's KASLR support remains very limited, making the kernel vulnerable to just-in-time (JIT) return-oriented programming (ROP) attacks. Furthermore, commodity OSs such as Linux restrict their KASLR range to 32 bits due to architectural constraints (e.g., x86-64 only supports 32-bit immediate operands for most instructions), which makes them vulnerable to even unsophisticated brute-force ROP attacks due to low entropy. Most in-kernel pointers remain static, exacerbating the problem when pointers are leaked.

Converged multi-level secure (MLS) systems, such as Qubes OS or SecureView, heavily rely on virtualization and service virtual machines (VMs). Traditionally, driver domains - isolated VMs that run device drivers - and daemon VMs use full-blown general-purpose OSs. It seems that specialized lightweight OSs, known as unikernels, would be a better fit for those. Surprisingly, to this day, driver domains can only be built from Linux. We discuss how unikernels can be beneficial in this context - they improve security and isolation, reduce memory overheads, and simplify software configuration and deployment. We specifically propose to use unikernels that borrow device drivers from existing general-purpose OSs.

The concurrency literature presents a number of approaches for building non-blocking, FIFO, multiple-producer and multiple-consumer (MPMC) queues. However, existing wait-free queues are either not very scalable or suffer from potentially unbounded memory usage. We present a wait-free queue, wCQ, which uses its own variation of the fast-path-slow-path methodology to attain wait-freedom and bound memory usage. wCQ is memory efficient and its performance is often on par with the best known concurrent queue designs.

The concurrency literature presents a number of approaches for building non-blocking, FIFO, multiple-producer and multiple-consumer (MPMC) queues. However, only a fraction of them have high performance. In addition, many queue designs, such as LCRQ, trade memory usage for better performance. The recently proposed SCQ design achieves both memory efficiency as well as excellent performance. Unfortunately, both LCRQ and SCQ are only lock-free. On the other hand, existing wait-free queues are either not very performant or suffer from potentially unbounded memory usage. Strictly described, the latter queues, such as Yang & Mellor-Crummey's (YMC) queue, forfeit wait-freedom as they are blocking when memory is exhausted. We present a wait-free queue, called wCQ. wCQ is based on SCQ and uses its own variation of fast-path-slow-path methodology to attain wait-freedom and bound memory usage. Our experimental studies on x86 and PowerPC architectures validate wCQ's great performance and memory efficiency. They also show that wCQ's performance is often on par with the best known concurrent queue designs.

We present a family of safe memory reclamation schemes, Hyaline, which are fast, scalable, and transparent to the underlying lock-free data structures. Hyaline is based on reference counting -- considered impractical for memory reclamation in the past due to high overheads. Hyaline uses reference counters only during reclamation, but not while accessing individual objects, which reduces overheads for object accesses. Since with reference counters, an arbitrary thread ends up freeing memory, Hyaline's reclamation workload is (almost) balanced across all threads, unlike most prior reclamation schemes such as epoch-based reclamation (EBR) or hazard pointers (HP). Hyaline often yields (excellent) EBR-grade performance with (good) HP-grade memory efficiency, which is a challenging trade-off with all existing schemes.

We present a new wait-free memory reclamation scheme, Crystalline, that simultaneously addresses the challenges of high performance, high memory efficiency, and wait-freedom. Crystalline guarantees complete wait-freedom even when threads are dynamically recycled, asynchronously reclaims memory in the sense that any thread can reclaim memory retired by any other thread, and ensures (an almost) balanced reclamation workload across all threads. The latter two properties result in Crystalline’s high performance and high memory efficiency, a difficult trade-off for most existing schemes. Our evaluations show that Crystalline exhibits outstanding scalability and memory efficiency, and achieves superior throughput than state-of-the-art reclamation schemes as the number of threads grows.

In this paper, we present a universal memory reclamation scheme, Wait-Free Eras (WFE), for deleted memory blocks in wait-free concurrent data structures. WFE's key innovation is that it is completely wait-free. Although some prior techniques provide similar guarantees for certain data structures, they lack support for arbitrary wait-free data structures. Consequently, developers are typically forced to marry their wait-free data structures with lock-free Hazard Pointers or (potentially blocking) epoch-based memory reclamation. Since both these schemes provide weaker progress guarantees, they essentially forfeit the strong progress guarantee of wait-free data structures. Though making the original Hazard Pointers scheme or epoch-based reclamation completely wait-free seems infeasible, we achieved this goal with a more recent, (lock-free) Hazard Eras scheme, which we extend to guarantee wait-freedom. As this extension is non-trivial, we discuss all challenges pertaining to the construction of universal wait-free memory reclamation.

We present LibrettOS, an OS design that fuses two paradigms to simultaneously address issues of isolation, performance, compatibility, failure recoverability, and run-time upgrades. LibrettOS acts as a microkernel OS that runs servers in an isolated manner. LibrettOS can also act as a library OS when, for better performance, selected applications are granted exclusive access to virtual hardware resources such as storage and networking. Furthermore, applications can switch between the two OS modes with no interruption at runtime. LibrettOS has a uniquely distinguishing advantage in that, the two paradigms seamlessly coexist in the same OS, enabling users to simultaneously exploit their respective strengths (i.e., greater isolation, high performance). Systems code, such as device drivers, network stacks, and file systems remain identical in the two modes, enabling dynamic mode switching and reducing development and maintenance costs.

We present a new lock-free safe memory reclamation algorithm, Hyaline, which is fast, scalable, and transparent to the underlying data structures. Hyaline easily handles virtually unbounded number of threads that can be created and deleted dynamically, while retaining O(1) reclamation cost. We also extend Hyaline to avoid situations where stalled threads prevent others from reclaiming newly allocated objects, a common problem with epoch-based reclamation. Our evaluation reveals that Hyaline's throughput is high -- it steadily outperformed other reclamation schemes by >10% in one test and yielded even higher gains in oversubscribed scenarios.

We present a new lock-free multiple-producer and multiple-consumer (MPMC) FIFO queue design which is scalable and, unlike existing high-performant queues, very memory efficient. Moreover, the design is ABA safe and does not require any external memory allocators or safe memory reclamation techniques, typically needed by other scalable designs. In fact, this queue itself can be leveraged for object allocation and reclamation, as in data pools. We use FAA (fetch-and-add), a specialized and more scalable than CAS (compare-and-set) instruction, on the most contended hot spots of the algorithm. However, unlike prior attempts with FAA, our queue is both lock-free and linearizable. We propose a general approach, SCQ, for bounded queues. This approach can easily be extended to support unbounded FIFO queues which can store an arbitrary number of elements. SCQ is portable across virtually all existing architectures and flexible enough for a wide variety of uses. We measure the performance of our algorithm on the x86-64 and PowerPC architectures. Our evaluation validates that our queue has exceptional memory efficiency compared to other algorithms and its performance is often comparable to, or exceeding that of state-of-the-art scalable algorithms.

Most operating systems provide protection and isolation to user processes, but not to critical system components such as device drivers or other system code. Consequently, failures in these components often lead to system failures. VirtuOS is an operating system that exploits a new method of decomposition to protect against such failures. VirtuOS exploits virtualization to isolate and protect vertical slices of existing OS kernels in separate service domains. Each service domain represents a partition of an existing kernel, which implements a subset of that kernel's functionality. Unlike competing solutions that merely isolate device drivers, or cannot protect from malicious and vulnerable code, VirtuOS provides full protection of isolated system components. VirtuOS's user library dispatches system calls directly to service domains using an exceptionless system call model, avoiding the cost of a system call trap in many cases.

Virtualization is a powerful technique used for variety of application domains, including emerging cloud environments that provide access to virtual machines as a service. Because of the interaction of virtual machines with multiple underlying software and hardware layers, the analysis of the performance of applications running in virtualized environments has been difficult. Moreover, performance analysis tools commonly used in native environments were not available in virtualized environments, a gap which our work closes.