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arXiv2021

Analytical Process Scheduling Optimization for Heterogeneous Multi-core Systems

In this paper, we propose the first optimum process scheduling algorithm for an increasingly prevalent type of heterogeneous multicore (HEMC) system that combines high-performance big cores and energy-efficient small cores with the same instruction-set architecture (ISA). Existing algorithms are all heuristics-based, and the well-known IPC-driven approach essentially tries to schedule high scaling factor processes on big cores. Our analysis shows that, for optimum solutions, it is also critical to consider placing long running processes on big cores. Tests of SPEC 2006 cases on various big-small core combinations show that our proposed optimum approach is up to 34% faster than the IPC-driven heuristic approach in terms of total workload completion time. The complexity of our algorithm is O(NlogN) where N is the number of processes. Therefore, the proposed optimum algorithm is practical for use.

cs.DC↗

arXiv2021

Report on the "The Future of the Shell" Panel at HotOS 2021

This document summarizes the challenges and possible research directions around the shell and its ecosystem, collected during and after the HotOS21 Panel on the future of the shell. The goal is to create a snapshot of what a number of researchers from various disciplines -- connected to the shell to varying degrees -- think about its future. We hope that this document will serve as a reference for future research on the shell and its ecosystem.

cs.OS↗

arXiv2021

SLO beyond the Hardware Isolation Limits

Performance isolation is a keystone for SLO guarantees with shared resources in cloud and datacenter environments. To meet SLO requirements, the state of the art relies on hardware QoS support (e.g., Intel RDT) to allocate shared resources such as last-level caches and memory bandwidth for co-located latency-critical applications. As a result, the number of latency-critical applications that can be deployed on a physical machine is bounded by the hardware allocation capability. Unfortunately, such hardware capability is very limited. For example, Intel Xeon E5 v3 processors support at most four partitions for last-level caches, i.e., at most four applications can have dedicated resource allocation. This paper discusses the feasibility and unexplored challenges of providing SLO guarantees beyond the limits of hardware capability. We present CoCo to show the feasibility and the benefits. CoCo schedules applications to time-share interference-free partitions as a transparent software layer. Our evaluation shows that CoCo outperforms non-partitioned and round-robin approaches by up to 9x and 1.2x.

cs.OS↗

arXiv2021

A Learning-based Approach Towards Automated Tuning of SSD Configurations

Thanks to the mature manufacturing techniques, solid-state drives (SSDs) are highly customizable for applications today, which brings opportunities to further improve their storage performance and resource utilization. However, the SSD efficiency is usually determined by many hardware parameters, making it hard for developers to manually tune them and determine the optimal SSD configurations. In this paper, we present an automated learning-based framework, named LearnedSSD, that utilizes both supervised and unsupervised machine learning (ML) techniques to drive the tuning of hardware configurations for SSDs. LearnedSSD automatically extracts the unique access patterns of a new workload using its block I/O traces, maps the workload to previously workloads for utilizing the learned experiences, and recommends an optimal SSD configuration based on the validated storage performance. LearnedSSD accelerates the development of new SSD devices by automating the hard-ware parameter configurations and reducing the manual efforts. We develop LearnedSSD with simple yet effective learning algorithms that can run efficiently on multi-core CPUs. Given a target storage workload, our evaluation shows that LearnedSSD can always deliver an optimal SSD configuration for the target workload, and this configuration will not hurt the performance of non-target workloads.

cs.AR↗

arXiv2021

Fast Bitmap Fit: A CPU Cache Line friendly memory allocator for single object allocations

Applications making excessive use of single-object based data structures (such as linked lists, trees, etc...) can see a drop in efficiency over a period of time due to the randomization of nodes in memory. This slow down is due to the ineffective use of the CPU's L1/L2 cache. We present a novel approach for mitigating this by presenting the design of a single-object memory allocator that preserves memory locality across randomly ordered memory allocations and deallocations.

cs.DS↗

arXiv2022

FlexTOE: Flexible TCP Offload with Fine-Grained Parallelism

FlexTOE is a flexible, yet high-performance TCP offload engine (TOE) to SmartNICs. FlexTOE eliminates almost all host data-path TCP processing and is fully customizable. FlexTOE interoperates well with other TCP stacks, is robust under adverse network conditions, and supports POSIX sockets. FlexTOE focuses on data-path offload of established connections, avoiding complex control logic and packet buffering in the NIC. FlexTOE leverages fine-grained parallelization of the TCP data-path and segment reordering for high performance on wimpy SmartNIC architectures, while remaining flexible via a modular design. We compare FlexTOE on an Agilio-CX40 to host TCP stacks Linux and TAS, and to the Chelsio Terminator TOE. We find that Memcached scales up to 38% better on FlexTOE versus TAS, while saving up to 81% host CPU cycles versus Chelsio. FlexTOE provides competitive performance for RPCs, even with wimpy SmartNICs. FlexTOE cuts 99.99th-percentile RPC RTT by 3.2$\times$ and 50% versus Chelsio and TAS, respectively. FlexTOE's data-path parallelism generalizes across hardware architectures, improving single connection RPC throughput up to 2.4$\times$ on x86 and 4$\times$ on BlueField. FlexTOE supports C and XDP programs written in eBPF. It allows us to implement popular data center transport features, such as TCP tracing, packet filtering and capture, VLAN stripping, flow classification, firewalling, and connection splicing.

cs.NI↗

arXiv2021

An O(1) algorithm for implementing the LFU cache eviction scheme

Cache eviction algorithms are used widely in operating systems, databases and other systems that use caches to speed up execution by caching data that is used by the application. There are many policies such as MRU (Most Recently Used), MFU (Most Frequently Used), LRU (Least Recently Used) and LFU (Least Frequently Used) which each have their advantages and drawbacks and are hence used in specific scenarios. By far, the most widely used algorithm is LRU, both for its $O(1)$ speed of operation as well as its close resemblance to the kind of behaviour that is expected by most applications. The LFU algorithm also has behaviour desirable by many real world workloads. However, in many places, the LRU algorithm is is preferred over the LFU algorithm because of its lower run time complexity of $O(1)$ versus $O(\log n)$. We present here an LFU cache eviction algorithm that has a runtime complexity of $O(1)$ for all of its operations, which include insertion, access and deletion(eviction).

cs.DS↗

arXiv2021

An Evaluation of WebAssembly and eBPF as Offloading Mechanisms in the Context of Computational Storage

As the volume of data that needs to be processed continues to increase, we also see renewed interests in near-data processing in the form of computational storage, with eBPF (extended Berkeley Packet Filter) being proposed as a vehicle for computation offloading. However, discussions in this regard have so far ignored viable alternatives, and no convincing analysis has been provided. As such, we qualitatively and quantitatively evaluated eBPF against WebAssembly, a seemingly similar technology, in the context of computation offloading. This report presents our findings.

cs.AR↗

arXiv2021

Safe and Practical GPU Acceleration in TrustZone

We present a holistic design for GPU-accelerated computation in TrustZone TEE. Without pulling the complex GPU software stack into the TEE, we follow a simple approach: record the CPU/GPU interactions ahead of time, and replay the interactions in the TEE at run time. This paper addresses the approach's key missing piece -- the recording environment, which needs both strong security and access to diverse mobile GPUs. To this end, we present a novel architecture called CODY, in which a mobile device (which possesses the GPU hardware) and a trustworthy cloud service (which runs the GPU software) exercise the GPU hardware/software in a collaborative, distributed fashion. To overcome numerous network round trips and long delays, CODY contributes optimizations specific to mobile GPUs: register access deferral, speculation, and metastate-only synchronization. With these optimizations, recording a compute workload takes only tens of seconds, which is up to 95% less than a naive approach; replay incurs 25% lower delays compared to insecure, native execution.

cs.DC↗

arXiv2021

EDF-Like Scheduling for Self-Suspending Real-Time Tasks

In real-time systems, schedulability tests are utilized to provide timing guarantees. However, for self-suspending task sets, current suspension-aware schedulability tests are limited to Task-Level Fixed-Priority~(TFP) scheduling or Earliest-Deadline-First~(EDF) with constrained-deadline task systems. In this work we provide a unifying schedulability test for the uniprocessor version of Global EDF-Like (GEL) schedulers and arbitrary-deadline task sets. A large body of existing scheduling algorithms can be considered as EDF-Like, such as EDF, First-In-First-Out~(FIFO), Earliest-Quasi-Deadline-First~(EQDF) and Suspension-Aware EDF~(SAEDF). Therefore, the unifying schedulability test is applicable to those algorithms. Moreover, the schedulability test can be applied to TFP scheduling as well. Our analysis is the first suspension-aware schedulability test applicable to arbitrary-deadline sporadic real-time task systems under Job-Level Fixed-Priority (JFP) scheduling, such as EDF. Moreover, it is the first unifying suspension-aware schedulability test framework that covers a wide range of scheduling algorithms. Through numerical simulations, we show that the schedulability test outperforms the state of the art for EDF under constrained-deadline scenarios. Moreover, we demonstrate the performance of different configurations under EQDF and SAEDF.

cs.OS↗

arXiv2022

KML: Using Machine Learning to Improve Storage Systems

Operating systems include many heuristic algorithms designed to improve overall storage performance and throughput. Because such heuristics cannot work well for all conditions and workloads, system designers resorted to exposing numerous tunable parameters to users -- thus burdening users with continually optimizing their own storage systems and applications. Storage systems are usually responsible for most latency in I/O-heavy applications, so even a small latency improvement can be significant. Machine learning (ML) techniques promise to learn patterns, generalize from them, and enable optimal solutions that adapt to changing workloads. We propose that ML solutions become a first-class component in OSs and replace manual heuristics to optimize storage systems dynamically. In this paper, we describe our proposed ML architecture, called KML. We developed a prototype KML architecture and applied it to two case studies: optimizing readahead and NFS read-size values. Our experiments show that KML consumes less than 4KB of dynamic kernel memory, has a CPU overhead smaller than 0.2%, and yet can learn patterns and improve I/O throughput by as much as 2.3x and 15x for two case studies -- even for complex, never-seen-before, concurrently running mixed workloads on different storage devices.

cs.OS↗

arXiv2022

Verifying and Optimizing Compact NUMA-Aware Locks on Weak Memory Models

Developing concurrent software is challenging, especially if it has to run on modern architectures with Weak Memory Models (WMMs) such as ARMv8, Power, or RISC-V. For the sake of performance, WMMs allow hardware and compilers to aggressively reorder memory accesses. To guarantee correctness, developers have to carefully place memory barriers in the code to enforce ordering among critical memory operations. While WMM architectures are growing in popularity, identifying the necessary and sufficient barriers of complex synchronization primitives is notoriously difficult. Unfortunately, publications often consider barriers to be just implementation details and omit them. In this technical note, we report our efforts in verifying the correctness of the Compact NUMA-Aware (CNA) lock algorithm on WMMs. The CNA lock is of special interest because it has been proposed as a new slowpath for Linux qspinlock, the main spinlock in Linux. Besides determining a correct and efficient set of barriers for the original CNA algorithm on WMMs, we investigate the correctness of Linux qspinlock and the latest Linux CNA patch (v15) on the memory models LKMM, ARMv8, and Power. Surprisingly, we have found that Linux qspinlock and, consequently, Linux CNA are incorrect according to LKMM, but are still correct when compiled to ARMv8 or Power.

cs.OS↗

arXiv2022

FlexOS: Towards Flexible OS Isolation

At design time, modern operating systems are locked in a specific safety and isolation strategy that mixes one or more hardware/software protection mechanisms (e.g. user/kernel separation); revisiting these choices after deployment requires a major refactoring effort. This rigid approach shows its limits given the wide variety of modern applications' safety/performance requirements, when new hardware isolation mechanisms are rolled out, or when existing ones break. We present FlexOS, a novel OS allowing users to easily specialize the safety and isolation strategy of an OS at compilation/deployment time instead of design time. This modular LibOS is composed of fine-grained components that can be isolated via a range of hardware protection mechanisms with various data sharing strategies and additional software hardening. The OS ships with an exploration technique helping the user navigate the vast safety/performance design space it unlocks. We implement a prototype of the system and demonstrate, for several applications (Redis/Nginx/SQLite), FlexOS' vast configuration space as well as the efficiency of the exploration technique: we evaluate 80 FlexOS configurations for Redis and show how that space can be probabilistically subset to the 5 safest ones under a given performance budget. We also show that, under equivalent configurations, FlexOS performs similarly or better than several baselines/competitors.

cs.OS↗

arXiv2021

Bento and the Art of Repeated Research

Bento provides a new approach to developing file systems, with safety and high-velocity development in mind. This is achieved by using Rust, a modern and memory-safe systems programming language, and by providing a framework to run a single file system implementation in kernel space with the VFS or in user space with FUSE. In this paper, the benchmarking experiments from the Bento paper are repeated. We fail to exactly reproduce the results of the Bento paper, but more or less find the same patterns albeit with more outlying results. Additionally we unsuccessfully run a standardized test suite, and expand the set of experiments with latency benchmarks and throughput benchmarks using a RAM block device. The latency benchmarks show that ext4 with journaling consistently outperforms Bento-fs and the RAM throughput benchmarks show no additional consistent performance pattern. During this experimentation, a set of 12 bugs was encountered and analyzed. We find that the ratio of memory related bugs is lower than other systems programming projects that use C as opposed to Rust, thus supporting the claims of the Bento framework.

cs.OS↗

arXiv2021

Slowing Down for Performance and Energy: An OS-Centric Study in Network Driven Workloads

This paper studies three fundamental aspects of an OS that impact the performance and energy efficiency of network processing: 1) batching, 2) processor energy settings, and 3) the logic and instructions of the OS networking paths. A network device's interrupt delay feature is used to induce batching and processor frequency is manipulated to control the speed of instruction execution. A baremetal library OS is used to explore OS path specialization. This study shows how careful use of batching and interrupt delay results in 2X energy and performance improvements across different workloads. Surprisingly, we find polling can be made energy efficient and can result in gains up to 11X over baseline Linux. We developed a methodology and a set of tools to collect system data in order to understand how energy is impacted at a fine-grained granularity. This paper identifies a number of other novel findings that have implications in OS design for networked applications and suggests a path forward to consider energy as a focal point of systems research.

cs.OS↗

arXiv2021

In-Kernel Control-Flow Integrity on Commodity OSes using ARM Pointer Authentication

This paper presents an in-kernel, hardware-based control-flow integrity (CFI) protection, called PAL, that utilizes ARM's Pointer Authentication (PA). It provides three important benefits over commercial, state-of-the-art PA-based CFIs like iOS's: 1) enhancing CFI precision via automated refinement techniques, 2) addressing hindsight problems of PA for in kernel uses such as preemptive hijacking and brute-forcing attacks, and 3) assuring the algorithmic or implementation correctness via post validation. PAL achieves these goals in an OS-agnostic manner, so could be applied to commodity OSes like Linux and FreeBSD. The precision of the CFI protection can be adjusted for better performance or improved for better security with minimal engineering efforts if a user opts in to. Our evaluation shows that PAL incurs negligible performance overhead: e.g., <1% overhead for Apache benchmark and 3~5% overhead for Linux perf benchmark on the latest Mac mini (M1). Our post-validation approach helps us ensure the security invariant required for the safe uses of PA inside the kernel, which also reveals new attack vectors on the iOS kernel. PAL as well as the CFI-protected kernels will be open sourced.

cs.CR↗

arXiv2021

New Mechanism for Fast System Calls

System calls have no place on the fast path of microsecond-scale systems. However, kernel bypass prevents the OS from controlling and supervising access to the hardware. In this paper we introduce the fastcall space, a new layer in the traditional OS architecture, that hosts fastcalls. A fastcall implements the fast path of a traditional kernel operation and can stay on the fast path, because the transition to the fastcall space is $\approx\times 15$ faster than to the kernel space. This way the OS does not give up the control over device access, whereas the applications maintain their performance.

cs.OS↗

arXiv2022

DiOS -- An Extended Reality Operating System for the Metaverse

Driven by the recent improvements in device and networks capabilities, Extended Reality (XR) is becoming more pervasive; industry and academia alike envision ambitious projects such as the metaverse. However, XR is still limited by the current architecture of mobile systems. This paper makes the case for an XR-specific operating system (XROS). Such an XROS integrates hardware-support, computer vision algorithms, and XR-specific networking as the primitives supporting XR technology. These primitives represent the physical-digital world as a single shared resource among applications. Such an XROS allows for the development of coherent and system-wide interaction and display methods, systematic privacy preservation on sensor data, and performance improvement while simplifying application development.

cs.HC↗