This document discusses various techniques for improving cache performance, including reducing the miss rate and miss penalty. It describes reducing misses through larger block sizes, higher associativity, victim caches, and prefetching. It also covers reducing miss penalties via read priority on misses, non-blocking caches, and adding a second level cache. The goal is to improve CPU performance by lowering the miss rate, miss penalty, and time to hit in the cache.
Supporting Time-Sensitive Applications on a Commodity OSNamHyuk Ahn
1) The document discusses Time-Sensitive Linux (TSL), which aims to support time-sensitive applications on commodity operating systems like Linux.
2) TSL improves kernel latency through an accurate timer mechanism called firm timers, a responsive kernel using lock-breaking preemption, and effective scheduling using proportion-based and priority-based algorithms.
3) Evaluation shows TSL reduces timer latency to under 1ms and preemption latency to under 1ms, improving synchronization of media playback under load compared to standard Linux.
This document discusses CPU scheduling algorithms and concepts. It provides definitions of preemptive versus nonpreemptive scheduling, describes how to calculate the number of possible schedules for n processes, and gives examples of average turnaround times for different scheduling algorithms like FCFS, SJF, and one that uses future knowledge. It also discusses parameters for scheduling algorithms, relations between different scheduling algorithms, and distinguishes between process-controlled and system-controlled scheduling.
This document discusses different CPU scheduling algorithms used in operating systems. It begins by explaining the assumptions made in early CPU scheduling research and goals of scheduling algorithms. It then covers First Come First Served (FCFS) scheduling and provides an example. Next it introduces Round Robin (RR) scheduling and compares it to FCFS. Shortest Job First (SJF) and Shortest Remaining Time First (SRTF) algorithms are presented as optimal approaches but difficult to implement due to lack of knowledge about future job lengths. The document concludes by discussing predicting future job behavior to improve scheduling decisions.
This document discusses techniques to improve the scalability of transactional memory systems. It analyzes issues that arise with scaling such systems to larger numbers of processors. It proposes using a value predictor to reduce conflicts and aborts in transactional memory, and presents initial results showing performance improvements. Further work is outlined to extend these techniques and better evaluate their effectiveness.
This document discusses Google's use of CRIU for task migration at scale. It provides background on Borg, Google's cluster management system, and how tasks run in isolated containers. CRIU is used to checkpoint and restore task state, allowing tasks to be migrated transparently to avoid evictions. While migrations currently take 1-2 minutes, work is ongoing to improve performance and implement live migration to support latency-sensitive tasks. Security around CRIU's use of privileges is also an area of focus. Overall, CRIU has worked well but continued collaboration is needed to address remaining challenges.
Improving Real-Time Performance on Multicore Platforms using MemGuardHeechul Yun
This document summarizes research on improving real-time performance on multicore platforms using MemGuard. It begins with an introduction to challenges in shared memory systems like unpredictable memory performance. It then presents MemGuard, which guarantees minimum memory bandwidth for each core through bandwidth reservation and best-effort sharing. A case study shows MemGuard improved real-time performance of a video capture task running with an X-server on an Intel Xeon system, eliminating deadline misses. The document concludes MemGuard can efficiently improve real-time performance but has limitations like coarse-grained enforcement that future work could address.
Supporting Time-Sensitive Applications on a Commodity OSNamHyuk Ahn
1) The document discusses Time-Sensitive Linux (TSL), which aims to support time-sensitive applications on commodity operating systems like Linux.
2) TSL improves kernel latency through an accurate timer mechanism called firm timers, a responsive kernel using lock-breaking preemption, and effective scheduling using proportion-based and priority-based algorithms.
3) Evaluation shows TSL reduces timer latency to under 1ms and preemption latency to under 1ms, improving synchronization of media playback under load compared to standard Linux.
This document discusses CPU scheduling algorithms and concepts. It provides definitions of preemptive versus nonpreemptive scheduling, describes how to calculate the number of possible schedules for n processes, and gives examples of average turnaround times for different scheduling algorithms like FCFS, SJF, and one that uses future knowledge. It also discusses parameters for scheduling algorithms, relations between different scheduling algorithms, and distinguishes between process-controlled and system-controlled scheduling.
This document discusses different CPU scheduling algorithms used in operating systems. It begins by explaining the assumptions made in early CPU scheduling research and goals of scheduling algorithms. It then covers First Come First Served (FCFS) scheduling and provides an example. Next it introduces Round Robin (RR) scheduling and compares it to FCFS. Shortest Job First (SJF) and Shortest Remaining Time First (SRTF) algorithms are presented as optimal approaches but difficult to implement due to lack of knowledge about future job lengths. The document concludes by discussing predicting future job behavior to improve scheduling decisions.
This document discusses techniques to improve the scalability of transactional memory systems. It analyzes issues that arise with scaling such systems to larger numbers of processors. It proposes using a value predictor to reduce conflicts and aborts in transactional memory, and presents initial results showing performance improvements. Further work is outlined to extend these techniques and better evaluate their effectiveness.
This document discusses Google's use of CRIU for task migration at scale. It provides background on Borg, Google's cluster management system, and how tasks run in isolated containers. CRIU is used to checkpoint and restore task state, allowing tasks to be migrated transparently to avoid evictions. While migrations currently take 1-2 minutes, work is ongoing to improve performance and implement live migration to support latency-sensitive tasks. Security around CRIU's use of privileges is also an area of focus. Overall, CRIU has worked well but continued collaboration is needed to address remaining challenges.
Improving Real-Time Performance on Multicore Platforms using MemGuardHeechul Yun
This document summarizes research on improving real-time performance on multicore platforms using MemGuard. It begins with an introduction to challenges in shared memory systems like unpredictable memory performance. It then presents MemGuard, which guarantees minimum memory bandwidth for each core through bandwidth reservation and best-effort sharing. A case study shows MemGuard improved real-time performance of a video capture task running with an X-server on an Intel Xeon system, eliminating deadline misses. The document concludes MemGuard can efficiently improve real-time performance but has limitations like coarse-grained enforcement that future work could address.
An extremely little set of rules to write good commit messages.
History (how code changes over time) become a very useful tool if associated with good commit messages.
These slides would make developers more aware about how good commit messages could improve their work.
The document discusses various scheduling algorithms used in operating systems including:
- First Come First Serve (FCFS) scheduling which services processes in the order they arrive but can lead to long wait times.
- Shortest Job First (SJF) scheduling which prioritizes the shortest processes first to minimize wait times. This can be preemptive or non-preemptive.
- Priority scheduling which assigns priorities to processes and services the highest priority first, which can cause starvation of low priority processes.
- Round Robin scheduling which allows fair sharing of the CPU by allocating a time quantum or slice to each process in a cyclic manner.
GCMA: Guaranteed Contiguous Memory AllocatorSeongJae Park
This document summarizes a presentation about GCMA, a Guaranteed Contiguous Memory Allocator for Linux kernels. GCMA aims to provide fast and guaranteed contiguous memory allocation while maintaining good memory utilization. It designates "discardable" pages used by frontswap and clean cache as secondary clients that can be quickly vacated from the reserved area. Evaluations show GCMA provides significantly faster allocation latency and system performance compared to CMA, especially under memory pressure or fragmentation. The presenter is working to upstream GCMA code and provide further evaluation results.
This document discusses various CPU scheduling algorithms. It describes non-preemptive and preemptive scheduling and covers scheduling algorithms like first-come first-served (FCFS), shortest job first (SJF), priority scheduling, round robin, multi-level queue scheduling, and multi-processor scheduling. It provides details on how each algorithm works and its advantages and disadvantages.
Operating Systems Process Scheduling Algorithmssathish sak
The document discusses various CPU scheduling algorithms used in operating systems including first-come, first-served (FCFS), round robin (RR), shortest job first (SJF), and shortest remaining time first (SRTF). It explains the assumptions, goals, and tradeoffs of each algorithm such as minimizing response time, maximizing throughput, and ensuring fairness. Examples are provided to illustrate how each algorithm works and its performance compared to others under different conditions involving job lengths. Predicting future job lengths is also discussed as it can impact the performance of algorithms like SRTF.
This document discusses various CPU scheduling algorithms including first-come first-served, shortest job first, priority scheduling, round robin scheduling, multilevel queue scheduling, multilevel feedback queue scheduling, and scheduling techniques for multiple processors and multicore processors. It provides examples and comparisons of how each algorithm works and considerations for optimization.
This document provides an outline of topics related to CPU scheduling in operating systems. It discusses basic concepts like CPU-I/O burst cycles, scheduling criteria, and various scheduling algorithms including first-come first-served, shortest job first, priority, round robin, and multilevel queue scheduling. It also covers thread scheduling, multiple processor scheduling, real-time scheduling, and approaches to evaluating scheduling algorithms.
The document discusses the Linux kernel memory model (LKMM). It provides an overview of LKMM, including that it defines ordering rules for the Linux kernel due to weaknesses in the C language standard and need to support multiple hardware architectures. It describes ordering primitives like atomic operations and memory barriers provided by LKMM and how the LKMM was formalized into an executable model that can prove properties of parallel code against the LKMM.
MemGuard: Memory Bandwidth Reservation System for Efficient Performance Isola...Heechul Yun
This document describes MemGuard, an operating system mechanism for providing efficient per-core memory performance isolation on commercial off-the-shelf hardware. MemGuard uses memory bandwidth reservation to guarantee each core's minimum memory bandwidth. It then performs predictive bandwidth donation and on-demand reclaiming to redistribute excess bandwidth, improving overall utilization. Evaluation shows MemGuard isolates performance and eliminates over 50% slowdown of a foreground real-time task due to interference, while maximizing throughput via bandwidth sharing.
This document discusses CPU scheduling in operating systems. It begins by introducing CPU scheduling and describing scheduling criteria such as CPU utilization, throughput, turnaround time, waiting time and response time. It then explains common scheduling algorithms like first-come first-served (FCFS), shortest job first (SJF), priority scheduling, and round robin (RR). The document also covers more advanced topics such as multilevel queue scheduling, real-time scheduling, thread scheduling, multiprocessor scheduling and examples of scheduling in Linux, Windows and Solaris.
Operating Systems 1 (10/12) - SchedulingPeter Tröger
The document discusses processes and scheduling in operating systems. It covers key concepts like processes, threads, scheduling criteria, and different scheduling algorithms like round robin and priority-based scheduling. It also discusses scheduling in multiprocessor systems and provides examples of scheduling in Windows.
This document summarizes key concepts in CPU scheduling, including:
1) CPU scheduling algorithms like FCFS, SJF, priority, and round robin and how they optimize different criteria.
2) The role of dispatchers in context switching between processes.
3) Scheduling criteria like CPU utilization, throughput, turnaround time.
4) Advanced scheduling techniques like multilevel queues, multilevel feedback queues, and multiprocessor scheduling.
Automatic NUMA balancing aims to improve performance on systems with Non-Uniform Memory Access (NUMA) by tracking where tasks access memory and placing tasks on nodes where their memory is located. It uses NUMA hinting page faults, page migration, task grouping, and fault statistics to determine optimal task placement. Pseudo-interleaving spreads tasks and memory across nodes to maximize memory bandwidth for workloads spanning multiple nodes. Evaluation shows automatic NUMA balancing can provide performance benefits for many workloads on NUMA systems without manual tuning.
The document discusses several topics related to CPU scheduling, including basic concepts, scheduling criteria, algorithms like first-come first-served (FCFS) and shortest-job-first (SJF), determining CPU burst lengths, priority scheduling, and approaches to scheduling on multiple processors. Key concepts are that the CPU scheduler selects ready processes to run and aims to maximize CPU utilization while minimizing waiting times using algorithms like FCFS, SJF, priority, and round robin scheduling. Load sharing and affinity are considerations for multiprocessor scheduling.
This document discusses cluster monitoring metrics and tools. It provides an introduction to metrics and monitoring, describes the Hadoop/HBase metrics framework including common metric types and examples. It then covers specific metrics for the master, region servers, JVM, RPCs and more. Finally it discusses tools like Ganglia, Nagios and JMX for collecting and viewing metrics and provides instructions for a hands-on exercise with Ganglia.
Slides de la présentation faite lors du PerfUG #3 du 29 août 2013 chez Octo Technology.
Sujet : comment déterminer rapidement les performances unitaires dont un système informatique est capable.
The document discusses several topics related to Linux containers including:
1. Managing the dentry cache to prevent it from being pinned and consuming all memory.
2. Checkpointing and restoring container tasks by freezing them, reading credentials and registers, and dumping memory.
3. Storing an entire container, including its files, in a single block device file to improve performance over using the host filesystem.
The document discusses various techniques to optimize computer memory performance. It begins by describing the memory hierarchy and characteristics of main memory technologies like SRAM and DRAM. It then discusses 11 advanced cache optimization techniques:
1) Using small, simple caches to reduce hit time.
2) Increasing cache bandwidth through techniques like pipelined, multibanked, and nonblocking caches.
3) Decreasing miss penalty through critical word first and merging write buffers.
4) Reducing miss rate via compiler optimizations and hardware/software prefetching.
The document analyzes each technique's impact on performance factors and implementation complexity. Generally, optimizations impact one factor but prefetching can reduce both misses and
Memory technology and optimization in Advance Computer ArchitechtureShweta Ghate
The document discusses various techniques to optimize computer memory performance. It begins by describing the memory hierarchy and characteristics of main memory technologies like SRAM and DRAM. It then discusses 11 advanced cache optimization techniques:
1) Using small, simple caches to reduce hit time.
2) Increasing cache bandwidth through techniques like pipelined, multibanked, and nonblocking caches.
3) Decreasing miss penalty through critical word first and merging write buffers.
4) Reducing miss rate via compiler optimizations and hardware/software prefetching.
The document analyzes each technique's impact on performance factors and implementation complexity. Generally, optimizations impact one factor but prefetching can reduce both misses and
An extremely little set of rules to write good commit messages.
History (how code changes over time) become a very useful tool if associated with good commit messages.
These slides would make developers more aware about how good commit messages could improve their work.
The document discusses various scheduling algorithms used in operating systems including:
- First Come First Serve (FCFS) scheduling which services processes in the order they arrive but can lead to long wait times.
- Shortest Job First (SJF) scheduling which prioritizes the shortest processes first to minimize wait times. This can be preemptive or non-preemptive.
- Priority scheduling which assigns priorities to processes and services the highest priority first, which can cause starvation of low priority processes.
- Round Robin scheduling which allows fair sharing of the CPU by allocating a time quantum or slice to each process in a cyclic manner.
GCMA: Guaranteed Contiguous Memory AllocatorSeongJae Park
This document summarizes a presentation about GCMA, a Guaranteed Contiguous Memory Allocator for Linux kernels. GCMA aims to provide fast and guaranteed contiguous memory allocation while maintaining good memory utilization. It designates "discardable" pages used by frontswap and clean cache as secondary clients that can be quickly vacated from the reserved area. Evaluations show GCMA provides significantly faster allocation latency and system performance compared to CMA, especially under memory pressure or fragmentation. The presenter is working to upstream GCMA code and provide further evaluation results.
This document discusses various CPU scheduling algorithms. It describes non-preemptive and preemptive scheduling and covers scheduling algorithms like first-come first-served (FCFS), shortest job first (SJF), priority scheduling, round robin, multi-level queue scheduling, and multi-processor scheduling. It provides details on how each algorithm works and its advantages and disadvantages.
Operating Systems Process Scheduling Algorithmssathish sak
The document discusses various CPU scheduling algorithms used in operating systems including first-come, first-served (FCFS), round robin (RR), shortest job first (SJF), and shortest remaining time first (SRTF). It explains the assumptions, goals, and tradeoffs of each algorithm such as minimizing response time, maximizing throughput, and ensuring fairness. Examples are provided to illustrate how each algorithm works and its performance compared to others under different conditions involving job lengths. Predicting future job lengths is also discussed as it can impact the performance of algorithms like SRTF.
This document discusses various CPU scheduling algorithms including first-come first-served, shortest job first, priority scheduling, round robin scheduling, multilevel queue scheduling, multilevel feedback queue scheduling, and scheduling techniques for multiple processors and multicore processors. It provides examples and comparisons of how each algorithm works and considerations for optimization.
This document provides an outline of topics related to CPU scheduling in operating systems. It discusses basic concepts like CPU-I/O burst cycles, scheduling criteria, and various scheduling algorithms including first-come first-served, shortest job first, priority, round robin, and multilevel queue scheduling. It also covers thread scheduling, multiple processor scheduling, real-time scheduling, and approaches to evaluating scheduling algorithms.
The document discusses the Linux kernel memory model (LKMM). It provides an overview of LKMM, including that it defines ordering rules for the Linux kernel due to weaknesses in the C language standard and need to support multiple hardware architectures. It describes ordering primitives like atomic operations and memory barriers provided by LKMM and how the LKMM was formalized into an executable model that can prove properties of parallel code against the LKMM.
MemGuard: Memory Bandwidth Reservation System for Efficient Performance Isola...Heechul Yun
This document describes MemGuard, an operating system mechanism for providing efficient per-core memory performance isolation on commercial off-the-shelf hardware. MemGuard uses memory bandwidth reservation to guarantee each core's minimum memory bandwidth. It then performs predictive bandwidth donation and on-demand reclaiming to redistribute excess bandwidth, improving overall utilization. Evaluation shows MemGuard isolates performance and eliminates over 50% slowdown of a foreground real-time task due to interference, while maximizing throughput via bandwidth sharing.
This document discusses CPU scheduling in operating systems. It begins by introducing CPU scheduling and describing scheduling criteria such as CPU utilization, throughput, turnaround time, waiting time and response time. It then explains common scheduling algorithms like first-come first-served (FCFS), shortest job first (SJF), priority scheduling, and round robin (RR). The document also covers more advanced topics such as multilevel queue scheduling, real-time scheduling, thread scheduling, multiprocessor scheduling and examples of scheduling in Linux, Windows and Solaris.
Operating Systems 1 (10/12) - SchedulingPeter Tröger
The document discusses processes and scheduling in operating systems. It covers key concepts like processes, threads, scheduling criteria, and different scheduling algorithms like round robin and priority-based scheduling. It also discusses scheduling in multiprocessor systems and provides examples of scheduling in Windows.
This document summarizes key concepts in CPU scheduling, including:
1) CPU scheduling algorithms like FCFS, SJF, priority, and round robin and how they optimize different criteria.
2) The role of dispatchers in context switching between processes.
3) Scheduling criteria like CPU utilization, throughput, turnaround time.
4) Advanced scheduling techniques like multilevel queues, multilevel feedback queues, and multiprocessor scheduling.
Automatic NUMA balancing aims to improve performance on systems with Non-Uniform Memory Access (NUMA) by tracking where tasks access memory and placing tasks on nodes where their memory is located. It uses NUMA hinting page faults, page migration, task grouping, and fault statistics to determine optimal task placement. Pseudo-interleaving spreads tasks and memory across nodes to maximize memory bandwidth for workloads spanning multiple nodes. Evaluation shows automatic NUMA balancing can provide performance benefits for many workloads on NUMA systems without manual tuning.
The document discusses several topics related to CPU scheduling, including basic concepts, scheduling criteria, algorithms like first-come first-served (FCFS) and shortest-job-first (SJF), determining CPU burst lengths, priority scheduling, and approaches to scheduling on multiple processors. Key concepts are that the CPU scheduler selects ready processes to run and aims to maximize CPU utilization while minimizing waiting times using algorithms like FCFS, SJF, priority, and round robin scheduling. Load sharing and affinity are considerations for multiprocessor scheduling.
This document discusses cluster monitoring metrics and tools. It provides an introduction to metrics and monitoring, describes the Hadoop/HBase metrics framework including common metric types and examples. It then covers specific metrics for the master, region servers, JVM, RPCs and more. Finally it discusses tools like Ganglia, Nagios and JMX for collecting and viewing metrics and provides instructions for a hands-on exercise with Ganglia.
Slides de la présentation faite lors du PerfUG #3 du 29 août 2013 chez Octo Technology.
Sujet : comment déterminer rapidement les performances unitaires dont un système informatique est capable.
The document discusses several topics related to Linux containers including:
1. Managing the dentry cache to prevent it from being pinned and consuming all memory.
2. Checkpointing and restoring container tasks by freezing them, reading credentials and registers, and dumping memory.
3. Storing an entire container, including its files, in a single block device file to improve performance over using the host filesystem.
The document discusses various techniques to optimize computer memory performance. It begins by describing the memory hierarchy and characteristics of main memory technologies like SRAM and DRAM. It then discusses 11 advanced cache optimization techniques:
1) Using small, simple caches to reduce hit time.
2) Increasing cache bandwidth through techniques like pipelined, multibanked, and nonblocking caches.
3) Decreasing miss penalty through critical word first and merging write buffers.
4) Reducing miss rate via compiler optimizations and hardware/software prefetching.
The document analyzes each technique's impact on performance factors and implementation complexity. Generally, optimizations impact one factor but prefetching can reduce both misses and
Memory technology and optimization in Advance Computer ArchitechtureShweta Ghate
The document discusses various techniques to optimize computer memory performance. It begins by describing the memory hierarchy and characteristics of main memory technologies like SRAM and DRAM. It then discusses 11 advanced cache optimization techniques:
1) Using small, simple caches to reduce hit time.
2) Increasing cache bandwidth through techniques like pipelined, multibanked, and nonblocking caches.
3) Decreasing miss penalty through critical word first and merging write buffers.
4) Reducing miss rate via compiler optimizations and hardware/software prefetching.
The document analyzes each technique's impact on performance factors and implementation complexity. Generally, optimizations impact one factor but prefetching can reduce both misses and
This document discusses cache memory and techniques to improve cache performance. It defines cache memory as a small, fast type of volatile memory that stores frequently accessed instructions and data to increase performance. The memory hierarchy is described, with cache memory sitting between the CPU and main memory. Factors that influence cache performance like cache hits, misses, and replacement policies for direct mapped caches are also outlined. Finally, methods for reducing cache miss rates and penalties are presented, such as using compiler optimizations, increasing cache size and associativity, adding multiple cache levels, and reducing cache hit times.
This document discusses optimizations to cache memory hierarchies to improve performance. It introduces the concepts of multi-level caches, where adding a second-level cache can reduce the miss penalty from the first-level cache. The average memory access time equation is extended to account for multiple cache levels. Examples are provided to show how a second-level cache can lower the average memory access time and reduce stalls per instruction compared to a single-level cache.
Lec10 Computer Architecture by Hsien-Hsin Sean Lee Georgia Tech -- Memory part2Hsien-Hsin Sean Lee, Ph.D.
This document summarizes a lecture on advanced computer architecture and memory hierarchy design techniques. It discusses cache penalty reduction techniques like victim caches and prefetching. It also covers virtual memory and address translation using page tables and translation lookaside buffers. Different cache organizations are described, including virtually and physically indexed caches. Solutions to problems like aliases and synonyms in virtual caches are also summarized.
Cache memory is used to improve performance by taking advantage of temporal and spatial locality in memory access patterns. There are typically three main types of cache misses: compulsory misses due to new data, capacity misses when the cache is too small, and conflict misses due to limited cache associativity. Cache design aims to reduce miss rates through greater associativity and larger size, and reduce miss penalties through faster memory and write buffers.
This document discusses cache hierarchies and techniques to improve cache performance. It covers types of cache misses like compulsory, capacity and conflict misses. Methods to reduce miss rates include using larger block sizes, caches and associativity. Victim caches and prefetching can help tolerate miss penalties. The document provides examples of Intel cache designs including a dual-core chip with private 12MB L3 caches and an 80-core prototype with an entire die of stacked SRAM cache. Non-uniform cache architectures are discussed as an approach for large multi-megabyte caches.
Computer System Architecture Lecture Note 8.1 primary MemoryBudditha Hettige
This document provides information about computer memory architecture. It discusses the memory hierarchy from registers to disk and describes the different levels of cache memory. It also covers topics like primary memory, virtual memory, RAM types (SRAM, DRAM, SDRAM), memory errors, parity checking, ECC, and magnetic disk storage.
This document discusses memory hierarchy and caching. It begins by describing the memory hierarchy pyramid from fastest and smallest (registers) to slowest and largest (disk). The key concepts of locality of reference—temporal and spatial locality—are introduced. Cache aims to exploit locality by storing recently accessed data in faster memory closer to the CPU. Direct mapping, set associative mapping, and fully associative mapping are described as techniques for mapping memory blocks to cache lines. Replacement policies for determining which cache line to overwrite are also discussed.
This document discusses memory hierarchy and caching. It can be summarized as follows:
1. Memory is organized in a hierarchy from fastest and smallest (registers and cache) to slowest and largest (disk). Cache sits between CPU and main memory to improve performance by exploiting locality of reference.
2. Caches use mapping functions to determine which block of main memory corresponds to each cache line. Direct mapping allocates blocks to lines in a fixed way while fully associative mapping allows blocks to map to any line.
3. Cache hits are faster than misses, which involve reading a block from lower levels. Hit rates above 95% can improve average memory access time significantly compared to lower hit rates.
The document discusses parallel computing platforms and techniques for hiding memory latency. It covers the following key points:
1) Implicit parallelism in microprocessors has increased through pipelining and superscalar execution, but memory latency remains a bottleneck. Caches help reduce effective latency by exploiting data locality.
2) Multithreading and prefetching are approaches to hide memory latency by keeping the processor occupied while waiting for data, but they increase bandwidth demands and hardware costs.
3) Different applications utilize different types of parallelism, like data-level parallelism for throughput or task-level parallelism for aggregate performance. Understanding performance bottlenecks is important for parallelization.
This document provides an overview of cache partitioning techniques (CPTs) in multicore processors. It begins with background on the motivation for CPTs due to increasing cache contention with more cores. It then covers various classifications of CPTs including granularity (way, set, block), static vs dynamic, strict vs pseudo, and hardware vs software control. It discusses challenges of CPTs like profiling overhead and complexity. It also covers techniques for profiling cache usage and determining optimal partitions. The goal of CPTs is to improve performance by reducing interference between applications sharing a cache.
Taming Non-blocking Caches to Improve Isolation in Multicore Real-Time SystemsHeechul Yun
In this paper, we show that cache partitioning does
not necessarily ensure predictable cache performance in modern
COTS multicore platforms that use non-blocking caches to exploit
memory-level-parallelism (MLP).
Through carefully designed experiments using three real COTS
multicore platforms (four distinct CPU architectures) and a cycleaccurate
full system simulator, we show that special hardware
registers in non-blocking caches, known as Miss Status Holding
Registers (MSHRs), which track the status of outstanding cachemisses,
can be a significant source of contention; we observe up
to 21X WCET increase in a real COTS multicore platform due
to MSHR contention.
We propose a hardware and system software (OS) collaborative
approach to efficiently eliminate MSHR contention for
multicore real-time systems. Our approach includes a low-cost
hardware extension that enables dynamic control of per-core
MLP by the OS. Using the hardware extension, the OS scheduler
then globally controls each core’s MLP in such a way that
eliminates MSHR contention and maximizes overall throughput
of the system.
We implement the hardware extension in a cycle-accurate fullsystem
simulator and the scheduler modification in Linux 3.14
kernel. We evaluate the effectiveness of our approach using a set
of synthetic and macro benchmarks. In a case study, we achieve
up to 19% WCET reduction (average: 13%) for a set of EEMBC
benchmarks compared to a baseline cache partitioning setup.
Memory system, and not processor speed, is often the bottleneck for many applications.
Memory system performance is largely captured by two parameters, latency and bandwidth.
Latency is the time from the issue of a memory request to the time the data is available at the processor.
Bandwidth is the rate at which data can be pumped to the processor by the memory system.
The document discusses memory hierarchies and cache performance. It explains that caches exploit locality by copying frequently accessed data from slower memory into faster caches. It then describes the basic structure of direct-mapped caches, including tags and valid bits. It also covers cache hits, misses, and replacement policies. Finally, it discusses techniques for measuring cache performance, including miss rates, miss penalties, and average memory access time.
Memory Hierarchy PPT of Computer Organization2022002857mbit
The document discusses memory hierarchy and cache design. It begins by listing sources used to create slides on this topic. It then provides definitions of key terms like cache hit, miss, hit time, and miss penalty. The document explains the principles of memory hierarchy, including exploiting locality of reference and implementing multiple memory levels with decreasing size but increasing speed. It discusses technologies like SRAM and DRAM that are commonly used for caches and main memory. The document also addresses four important questions in cache design: block placement, block identification, block replacement, and write strategy.
Preparing Codes for Intel Knights Landing (KNL)AllineaSoftware
The document discusses preparing codes to take advantage of the Intel Knights Landing (KNL) processor. It outlines three main steps:
1. Use Allinea Performance Reports to analyze memory access and identify optimization opportunities like improving cache usage or increasing thread count.
2. If memory access is identified as a bottleneck, improve cache usage through techniques like blocking or increase thread count to hide latency. The KNL processor includes high bandwidth memory (HBM) that codes should leverage.
3. Identify loops dominating execution time using Allinea MAP and apply vectorization either through compiler flags or manual techniques. Vectorization is key to exploiting the KNL's processing capabilities.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.