We report on our experience with the hardware transactional memory (HTM) feature of two pre-production revisions of a new commercial multicore processor. Our experience includes a number of promising results using HTM to improve performance in a variety of contexts, and also identifies some ways in which the feature could be improved to make it even better. We give detailed accounts of our experiences, sharing techniques we used to achieve the results we have, as well as describing challenges we faced in doing so.

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Early experience with a commercial hardware transactional memory implementation

An apparatus, system, and method are disclosed for managing eviction of data. A cache write module stores data on a non-volatile storage device sequentially using a log-based storage structure having a head region and a tail region. A direct cache module caches data on the non-volatile storage device using the log-based storage structure. The data is associated with storage operations between a host and a backing store storage device. An eviction module evicts data of at least one region in succession from the log-based storage structure starting with the tail region and progressing toward the head region.

Apparatus, system, and method for managing eviction of data

Research on transient execution attacks including Spectre and Meltdown showed that exception or branch misprediction events might leave secret-dependent traces in the CPU's microarchitectural state. This observation led to a proliferation of new Spectre and Meltdown attack variants and even more ad-hoc defenses (e.g., microcode and software patches). Both the industry and academia are now focusing on finding effective defenses for known issues. However, we only have limited insight on residual attack surface and the completeness of the proposed defenses. 
In this paper, we present a systematization of transient execution attacks. Our systematization uncovers 6 (new) transient execution attacks that have been overlooked and not been investigated so far: 2 new exploitable Meltdown effects: Meltdown-PK (Protection Key Bypass) on Intel, and Meltdown-BND (Bounds Check Bypass) on Intel and AMD; and 4 new Spectre mistraining strategies. We evaluate the attacks in our classification tree through proof-of-concept implementations on 3 major CPU vendors (Intel, AMD, ARM). Our systematization yields a more complete picture of the attack surface and allows for a more systematic evaluation of defenses. Through this systematic evaluation, we discover that most defenses, including deployed ones, cannot fully mitigate all attack variants.

A Systematic Evaluation of Transient Execution Attacks and Defenses

Serverless containers and functions are widely used for deploying and managing software in the cloud. Their popularity is due to reduced cost of operations, improved utilization of hardware, and faster scaling than traditional deployment methods. The economics and scale of serverless applications demand that workloads from multiple customers run on the same hardware with minimal overhead, while preserving strong security and performance isolation. The traditional view is that there is a choice between virtualization with strong security and high overhead, and container technologies with weaker security and minimal overhead. This tradeoff is unacceptable to public infrastructure providers, who need both strong security and minimal overhead. To meet this need, we developed Firecracker, a new open source Virtual Machine Monitor (VMM) specialized for serverless workloads, but generally useful for containers, functions and other compute workloads within a reasonable set of constraints. We have deployed Firecracker in two publically-available serverless compute services at Amazon Web Services (Lambda and Fargate), where it supports millions of production workloads, and trillions of requests per month. We describe how specializing for serverless informed the design of Firecracker, and what we learned from seamlessly migrating Lambda customers to Firecracker.

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Firecracker: Lightweight virtualization for serverless applications

An apparatus, system, and method are disclosed for destaging cached data. A cache controller (116) detects one or more write requests to store data in a backing store (118). The cache controller (116) sends the write requests to a storage controller (104) for a nonvolatile solid-state storage device (102). The storage controller (104) receives the write requests and caches the data in the storage device (102) by appending the data to a log (940) of the storage device (102). The log (940) includes a sequential, log-based structure preserved in the storage device (102). The cache controller (116) receives at least a portion of the data from the storage controller (104) in an order favoring operation of the storage device (102) and destages the data to the backing store (118) in that order, which is selected so that operation of the storage device (102) is more efficient in response to destaging.

Apparatus, system, and method for destaging cached data

The Complete Guide to Optimizing Systems Performance Written by the winner of the2013 LISA Award for Outstanding Achievement in System Administration Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux and Unix performance, while illuminating performance issues that are relevant to all operating systems. Youll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu, Fedora, CentOS, and the illumos-based Joyent SmartOS and OmniTI OmniOS. He systematically covers modern systems performance, including the traditional analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the unknown unknowns of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf Kernel internals: uncovering what the OS is doing Using system observability tools, interfaces, and frameworks Understanding and monitoring application performance Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators File system I/O, including caching Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O Network-related performance issues: protocols, sockets, interfaces, and physical connections Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Greggs extensive instructional experience.

Systems Performance: Enterprise and the Cloud

Systems, methods, and media for generating heat maps of event data are provided herein. Methods may include gathering instances of event data according to a performance characteristic, discretely decomposing the instances by applying at least one constraint to the instances, assigning a hue to each instance, the hue being associated with the at least one constraint, and generating a heat map that includes representations of the instances, wherein each representation includes the hue associated with the at least one constraint to which the instance has been assigned.

Systems, Methods, and Media for Generating Multidimensional Heat Maps

This visualization of software execution is a new necessity for performance profiling and debugging.

The flame graph

The Oracle Solaris DTrace feature revolutionizes the way you debug operating systems and applications. Using DTrace, you can dynamically instrument software and quickly answer virtually any question about its behavior. Now, for the first time, there's a comprehensive, authoritative guide to making the most of DTrace in any supported UNIX environment--from Oracle Solaris to OpenSolaris, Mac OS X, and FreeBSD. Written by key contributors to the DTrace community, DTrace teaches by example, presenting scores of commands and easy-to-adapt, downloadable D scripts. These concise examples generate answers to real and useful questions, and serve as a starting point for building more complex scripts. Using them, you can start making practical use of DTrace immediately, whether you're an administrator, developer, analyst, architect, or support professional. The authors fully explain the goals, techniques, and output associated with each script or command. Drawing on their extensive experience, they provide strategy suggestions, checklists, and functional diagrams, as well as a chapter of advanced tips and tricks. You'll learn how to Write effective scripts using DTrace's D language Use DTrace to thoroughly understand system performance Expose functional areas of the operating system, including I/O, filesystems, and protocols Use DTrace in the application and database development process Identify and fix security problems with DTrace Analyze the operating system kernel Integrate DTrace into source code Extend DTrace with other tools This book will help you make the most of DTrace to solve problems more quickly and efficiently, and build systems that work faster and more reliably.

Dtrace: Dynamic Tracing in Oracle Solaris, Mac OS X and Freebsd

It sounds good when knowing the solaris performance and tools dtrace and mdb techniques for solaris 10 and opensolaris in this website. This is one of the books that many people looking for. In the past, many people ask about this book as their favourite book to read and collect. And now, we present hat you need quickly. It seems to be so happy to offer you this famous book. It will not become a unity of the way for you to get amazing benefits at all. But, it will serve something that will let you get the best time and moment to spend for reading the book.

Brendan Gregg

Papers

Systems Performance: Enterprise and the Cloud

Systems, Methods, and Media for Generating Multidimensional Heat Maps

The flame graph

Dtrace: Dynamic Tracing in Oracle Solaris, Mac OS X and Freebsd

Solaris Performance and Tools: Dtrace and Mdb Techniques for Solaris 10 and Opensolaris