Expert insights. Personalized for you.
database big data performance benchmarking performance analysis redis alternative ec2 image ec2stack hardware news keydbWe've always been excited about Arm so when Amazon offered us early access to their new Arm-based instances we jumped at the chance to see what they could do. MORE
The fail-over condition arises due to uncontrolled network failure, OS failure, hardware failure or DR drill. Reducing time for disaster recovery is crucial for organizations needing to achieve operational resiliency. MORE
These systems are a combination of different hardware and software which have been configured to perform the desired task. Configuration testing is performed to discover the optimum combinations of software and hardware specifications that allow the system to work without flaws. MORE
performance c++ programming languages core java computing computer hardware programming & design complexity metrics optimization and algorithmic aspects platform independenceAs a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application. MORE
For example, you can monitor the behavior of your applications, the hardware usage of your server nodes, or even the network traffic between servers. One prominent solution is the open-source tool Nagios which allows you to monitor hardware in every detail. Introduction. MORE
Hardware infrastructure. This is a guest post by Hugues Alary , Lead Engineer at Betabrand , a retail clothing company and crowdfunding platform, based in San Francisco. This article was originally published here. Early infrastructure. Rackspace. The scalability and maintainability issue. Scaling development processes. The advent of Docker. Kubernetes. Learning Kubernetes. Officially migrating. The development/staging environments. A year after. kubernetes MORE
This channel is the perfect blend of programming, hardware, engineering, and crazy. Hey, HighScalability is back! After watching you’ll feel inadequate, but in an entertained sort of way. Love this Stuff? I need your support on Patreon to keep this stuff going. MORE
Hardware - servers/storage hardware/software faults such as disk failure, disk full, other hardware failures, servers running out of allocated resources, server software behaving abnormally, intra DC network connectivity issues, etc. MORE
HPU: Holographic Processing Unit (HPU) is the specific hardware of Microsoft’s Hololens. SPU: Stream Processing Unit (SPU) is related to the specialized hardware to process the data streams of video. TPU: Tensor Processing Unit (TPU) is Google’s specialized hardware for neural network. Movidius, which was acquired by Intel in 2016, develops its VPU-series named Myriad which makes hardware optimization for computer vision tasks. MORE
Cluster management, a common software infrastructure among technology companies, aggregates compute resources from a collection of physical hosts into a shared resource pool, amplifying compute power and allowing for the flexible use of data center hardware. Architecture Apache Hadoop Apache Spark Big Data Capacity Planning Cassandra Cluster Management Data Center Hardware MySQL Peloton Redis Uber Uber Engineering Unified Resource Scheduler Workload Cluster MORE
Adaptive Loading is a pattern for delivering a fast core experience to all users (including low-end devices) where you progressively add high-end-only features, if a user's network and hardware can handle it MORE
Byte-addressable non-volatile memory,) NVM will fundamentally change the way hardware interacts, the way operating systems are designed, and the way applications operate on data. " Uncategorized Hardware Operating SystemsA persistent problem: managing pointers in NVM Bittman et al., MORE
This is the first post in a series of posts on different approaches to systems security especially as they apply to hardware and architectural security. The class of techniques described in this blog post, which we broadly refer to as applied hardware and architecture cryptography, apply proven cryptographic techniques to strengthen systems. Naively securing this system would require a large amount of trust; “guns and guards”, trusted personnel, and trusted software and hardware. MORE
Most Intel microprocessors support “HyperThreading” (Intel’s trademark for their implementation of “simultaneous multithreading”) — which allows the hardware to support (typically) two “Logical Processors” for each physical core. Last year I was trying to diagnose a mild slowdown in a code, and wanted to be able to use the hardware performance counters to divide processor activity into four categories: Neither Logical Processor active. MORE
Uncategorized Algorithms and data structures HardwareEfficient lock-free durable sets Zuriel et al., OOPSLA’19. Given non-volatile memory (NVRAM), the naive hope for persistence is that it would be a no-op: what happens in memory, stays in memory. MORE
… to realize these insights, hardware needs to access data at object granularity and must have control over pointers between objects. Hotpads is a hardware-managed hierarchy of scratchpad-like memories called pads. Collection evictions that move objects up the hierarchy occur entirely in hardware and are much faster than software GT because pads are small. Uncategorized Hardware Operating Systems MORE
According to Dr. Bandwidth, performance analysis has two recurring themes: How fast should this code (or “simple” variations on this code) run on this hardware? This can start with either a “top-down” or “bottom-up” approach, but in complex codes running on complex hardware, what is really required is both approaches — iterated until the interactions between all the components are understood. The networking hardware. MORE
Hardware performance counter results for a simple benchmark code calling Intel’s optimized DGEMM implementation for this processor (from the Intel MKL library) show that about 20% of the dynamic instruction count consists of instructions that are not packed SIMD operations (i.e., This is an uninspiring fraction of peak performance that would normally suggest significant inefficiencies in either the hardware or software. MORE
Hardware Past As Performance Prologue. Regardless, the overall story for hardware progress remains grim, particularly when we recall how long device replacement cycles are: Tap for a larger version. MORE
Cache Coherence Implementations Computer Architecture Computer Hardware Performance memory bandwidth memory latency Xeon PhiThe Xeon Phi x200 (Knights Landing) has a lot of modes of operation (selected at boot time), and the latency and bandwidth characteristics are slightly different for each mode. MORE
Two of the main reasons we hear are often due to migration of hardware, or the need to split data between servers. Migrating ScaleGrid for Redis™ data from one server to another is a common requirement that we hear from our customers. MORE
It seems very likely that the hardware has to be able to merge these two load operations into a single L1 Data Cache access to keep the rate of cache accesses from being the performance bottleneck. But 2 32-bit loads is only 1/8 of a natural 512-bit cache access, and it seems unlikely that the hardware can merge cache accesses across multiple cycles. Algorithms Computer Architecture Computer Hardware Performance arithmetic high performance computing microprocessors MORE
Computer Architecture Computer Hardware Performance cache DRAM high performance computing memory bandwidth memory latency STREAM benchmark“Memory Bandwidth and System Balance in HPC Systems” If you are planning to attend the SuperComputing 2016 conference in Salt Lake City next month, be sure to reserve a spot on your calendar for my talk on Wednesday afternoon (4:15pm-5:00pm). MORE
We know that getting full computational performance out of most machines—nearly all desktops and laptops, most game consoles, and the newest smartphones—already means harnessing local parallel hardware, mainly in the form of multicore CPU processing. You can expect the above keynote to be, well, keynote-y… oriented toward software product features and of course AMD’s hardware, with plenty of forward-looking industry vision style material. MORE
An important concern in optimizing the hardware platform is hardware components that restrict performance, known as bottlenecks. General DBA Performance Tuning hardwareQuite often, the problem isn’t correcting performance bottlenecks as much as it is identifying them in the first place. Start with obtaining a performance baseline. You monitor the server over time so that you can determine Server average […]. MORE
Portable: It allows shipping a single EXE that can use any combination of GPU vendors’ hardware. The initial implementation uses DirectCompute and supports all devices that are DX11 capable; DirectCompute is just an implementation detail of the first release, and the model can (and I expect will) be implemented to directly talk to any interesting hardware. More to come… C++ Concurrency Hardware Microsoft Software Development Talks & Events MORE
This has not only led to AI acceleration being incorporated into common chip architectures such as CPUs, GPUs, and FPGAs but also mushroomed a class of dedicated hardware AI accelerators specifically designed to accelerate artificial neural networks and machine learning applications. MORE
The underlying SIMD hardware is exposed via instructions such as SSE, AVX, AVX2, AVX-512, and those in the Intel® Xe Architecture Gen12 ISA. Introduction. Modern CPU and GPU cores use single instruction, multiple data (SIMD) execution units to achieve higher performance and power efficiency. MORE
Don’t trust hardware or software; then you can build trustworthy hardware and software. Hardware Software DevelopmentJames Hamilton on how to write reliable software in a world where anything that can fail, will fail. MORE
Now welcome to the hardware jungle. For the first time in the history of computing, mainstream hardware is no longer a single-processor von Neumann machine, and never will be again. Concurrency Hardware Opinion & Editorial Software DevelopmentWith so much happening in the computing world, now seemed like the right time to write “Welcome to the Jungle” – a sequel to my earlier “The Free Lunch Is Over” essay. Here’s the introduction: Welcome to the Jungle. MORE
EWR is the ratio of bytes issue by the iMC divided by the number of bytes actually written to the 3D-XPoint media (as measured by the DIMM’s hardware counters). Uncategorized Hardware PerformanceAn empirical guide to the behavior and use of scalable persistent memory , Yang et al., MORE
The very flexible nature of the technology opens many doors, including business collaborations, reuse in third-party products, or even conquering hardware barriers by reaching a spectrum of devices. Introduction. APIs — the current “big thing” — offer the opportunity for modern organizations to unlock new and lucrative business models. The article below covers some tips on how to spin the API flywheel and leverage its possibilities. MORE
SQL Server Performance Tuning can be a difficult assignment, especially when working with a massive database where even the minor change can raise a significant impact on the existing query performance. MORE
But what is the metric that shows service hardware monopolization by a group of users? Scenario. Any service provider tries to reach several metrics in their activity. One group of these metrics is service quality. Quality metrics contain: The ratio of successfully processed requests. MORE
Now welcome to the hardware jungle. Concurrency Hardware Software Development Talks & Events WebLast month in Kansas City I gave a talk on “Welcome to the Jungle,” based on my recent essay of the same name (sequel to “The Free Lunch Is Over”) concerning the turn to mainstream heterogeneous distributed computing and the end of Moore’s Law. MORE
An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., The paper examines the implications of microservices at the hardware, OS and networking stack, cluster management, and application framework levels, as well as the impact of tail latency. Hardware implications. ASPLOS’19. MORE
Storage Hardware and Devices nvme optaneThe easiest way to identify NVME drives backed by either NAND flash or Optane is to use $ lspci -v The output will look like this for NVME/NAND 00:0d.0 MORE
So we need low latency, but we also need very high throughput: A recurring theme in IDS/IPS literature is the gap between the workloads they need to handle and the capabilities of existing hardware/software implementations. Uncategorized Hardware Networking MORE
Mainstream hardware – many kinds of parallelism: What’s the relationship among multi-core CPUs, hardware threads , SIMD vector units (Intel SSE and AVX , ARM Neon ), and GPGPU (general-purpose computation on GPUs, which I covered at C++ and Beyond 2011 )? Task and data parallelism: What’s the difference between task parallelism and data parallelism, which kind of of hardware does each allow you to exploit, and why? MORE
Cluster management, a common software infrastructure among technology companies, aggregates compute resources from a collection of physical hosts into a shared resource pool, amplifying compute power and allowing for the flexible use of data center hardware. Architecture Apache Hadoop Apache Spark Big Data Capacity Planning Cassandra Cluster Management Data Center Hardware MySQL Peloton Redis Uber Uber Engineering Unified Resource Scheduler Workload Cluster MORE
The goal is to produce a low-energy hardware classifier for embedded applications doing local processing of sensor data. Race logic has four primary operations that are easy to implement in hardware: MAX, MIN, ADD-CONSTANT, and INHIBIT. One efficient way of doing that in analog hardware is the use of current-starved inverters. Uncategorized Hardware Machine LearningBoosted race trees for low energy classification Tzimpragos et al., ASPLOS’19. MORE
Now welcome to the hardware jungle. Cloud Concurrency Hardware Software Development Talks & EventsWhile visiting Facebook earlier this month, I gave a shorter version of my “Welcome to the Jungle” talk, based on the eponymous WttJ article. They made a nice recording and it’s now available online here: Facebook Engineering. Title: Herb Sutter: Welcome to the Jungle. MORE
Architecture Capacity Capacity Safety Hardware Capacity Planning Reliability site reliability engineering SRE Uber Eng Uber EngineeringReliability engineering teams at Uber build the tools, libraries, and infrastructure that enable engineers to operate our thousands of microservices reliably at scale. MORE
atomic<> Weapons: The C++11 Memory Model and Modern Hardware. Achingly, heartbreakingly clear, because some hardware incents you to pull out the big guns to achieve top performance, and C++ programmers just are so addicted to full performance that they’ll reach for the big red levers with the flashing warning lights. We’ll include clear answers to several FAQs: “how do the compiler and hardware cooperate to remember how to respect these rules?”, “what is a race condition?”, MORE
Hardware Related Topics SQL Shack
APRIL 14, 2020
SQL Server Performance Tuning can be a difficult assignment, especially when working with a massive database where even the minor change can raise a significant impact on the existing query performance.
SQL Server Performance
MARCH 12, 2019
An important concern in optimizing the hardware platform is hardware components that restrict performance, known as bottlenecks. General DBA Performance Tuning hardwareQuite often, the problem isn’t correcting performance bottlenecks as much as it is identifying them in the first place. Start with obtaining a performance baseline. You monitor the server over time so that you can determine Server average […].
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
The Morning Paper
MAY 12, 2019
An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., The paper examines the implications of microservices at the hardware, OS and networking stack, cluster management, and application framework levels, as well as the impact of tail latency. Hardware implications. ASPLOS’19.
John McCalpin
SEPTEMBER 17, 2018
Most Intel microprocessors support “HyperThreading” (Intel’s trademark for their implementation of “simultaneous multithreading”) — which allows the hardware to support (typically) two “Logical Processors” for each physical core. Last year I was trying to diagnose a mild slowdown in a code, and wanted to be able to use the hardware performance counters to divide processor activity into four categories: Neither Logical Processor active.
Sutter's Mill
JUNE 29, 2012
atomic<> Weapons: The C++11 Memory Model and Modern Hardware. Achingly, heartbreakingly clear, because some hardware incents you to pull out the big guns to achieve top performance, and C++ programmers just are so addicted to full performance that they’ll reach for the big red levers with the flashing warning lights. We’ll include clear answers to several FAQs: “how do the compiler and hardware cooperate to remember how to respect these rules?”, “what is a race condition?”,
DZone
FEBRUARY 27, 2021
performance c++ programming languages core java computing computer hardware programming & design complexity metrics optimization and algorithmic aspects platform independenceAs a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application.
The Morning Paper
NOVEMBER 15, 2020
So we need low latency, but we also need very high throughput: A recurring theme in IDS/IPS literature is the gap between the workloads they need to handle and the capabilities of existing hardware/software implementations. Uncategorized Hardware Networking
n0derunner
JULY 15, 2020
Storage Hardware and Devices nvme optaneThe easiest way to identify NVME drives backed by either NAND flash or Optane is to use $ lspci -v The output will look like this for NVME/NAND 00:0d.0
ACM Sigarch
APRIL 26, 2018
HPU: Holographic Processing Unit (HPU) is the specific hardware of Microsoft’s Hololens. SPU: Stream Processing Unit (SPU) is related to the specialized hardware to process the data streams of video. TPU: Tensor Processing Unit (TPU) is Google’s specialized hardware for neural network. Movidius, which was acquired by Intel in 2016, develops its VPU-series named Myriad which makes hardware optimization for computer vision tasks.
Uber Engineering
MARCH 7, 2019
Architecture Capacity Capacity Safety Hardware Capacity Planning Reliability site reliability engineering SRE Uber Eng Uber EngineeringReliability engineering teams at Uber build the tools, libraries, and infrastructure that enable engineers to operate our thousands of microservices reliably at scale.
Uber Engineering
OCTOBER 30, 2018
Cluster management, a common software infrastructure among technology companies, aggregates compute resources from a collection of physical hosts into a shared resource pool, amplifying compute power and allowing for the flexible use of data center hardware. Architecture Apache Hadoop Apache Spark Big Data Capacity Planning Cassandra Cluster Management Data Center Hardware MySQL Peloton Redis Uber Uber Engineering Unified Resource Scheduler Workload Cluster
Scalegrid
NOVEMBER 25, 2021
Two of the main reasons we hear are often due to migration of hardware, or the need to split data between servers. Migrating ScaleGrid for Redis™ data from one server to another is a common requirement that we hear from our customers.
The Morning Paper
MARCH 17, 2020
EWR is the ratio of bytes issue by the iMC divided by the number of bytes actually written to the 3D-XPoint media (as measured by the DIMM’s hardware counters). Uncategorized Hardware PerformanceAn empirical guide to the behavior and use of scalable persistent memory , Yang et al.,
The Morning Paper
MAY 23, 2019
… to realize these insights, hardware needs to access data at object granularity and must have control over pointers between objects. Hotpads is a hardware-managed hierarchy of scratchpad-like memories called pads. Collection evictions that move objects up the hierarchy occur entirely in hardware and are much faster than software GT because pads are small. Uncategorized Hardware Operating Systems
The Morning Paper
DECEMBER 8, 2019
Byte-addressable non-volatile memory,) NVM will fundamentally change the way hardware interacts, the way operating systems are designed, and the way applications operate on data. " Uncategorized Hardware Operating SystemsA persistent problem: managing pointers in NVM Bittman et al.,
The Morning Paper
DECEMBER 1, 2019
Uncategorized Algorithms and data structures HardwareEfficient lock-free durable sets Zuriel et al., OOPSLA’19. Given non-volatile memory (NVRAM), the naive hope for persistence is that it would be a no-op: what happens in memory, stays in memory.
ACM Sigarch
OCTOBER 4, 2018
This is the first post in a series of posts on different approaches to systems security especially as they apply to hardware and architectural security. The class of techniques described in this blog post, which we broadly refer to as applied hardware and architecture cryptography, apply proven cryptographic techniques to strengthen systems. Naively securing this system would require a large amount of trust; “guns and guards”, trusted personnel, and trusted software and hardware.
John McCalpin
AUGUST 1, 2018
According to Dr. Bandwidth, performance analysis has two recurring themes: How fast should this code (or “simple” variations on this code) run on this hardware? This can start with either a “top-down” or “bottom-up” approach, but in complex codes running on complex hardware, what is really required is both approaches — iterated until the interactions between all the components are understood. The networking hardware.
The Morning Paper
MAY 28, 2019
The goal is to produce a low-energy hardware classifier for embedded applications doing local processing of sensor data. Race logic has four primary operations that are easy to implement in hardware: MAX, MIN, ADD-CONSTANT, and INHIBIT. One efficient way of doing that in analog hardware is the use of current-starved inverters. Uncategorized Hardware Machine LearningBoosted race trees for low energy classification Tzimpragos et al., ASPLOS’19.
Uber Engineering
OCTOBER 30, 2018
Cluster management, a common software infrastructure among technology companies, aggregates compute resources from a collection of physical hosts into a shared resource pool, amplifying compute power and allowing for the flexible use of data center hardware. Architecture Apache Hadoop Apache Spark Big Data Capacity Planning Cassandra Cluster Management Data Center Hardware MySQL Peloton Redis Uber Uber Engineering Unified Resource Scheduler Workload Cluster
Sutter's Mill
FEBRUARY 26, 2012
Don’t trust hardware or software; then you can build trustworthy hardware and software. Hardware Software DevelopmentJames Hamilton on how to write reliable software in a world where anything that can fail, will fail.
DZone
APRIL 26, 2022
This has not only led to AI acceleration being incorporated into common chip architectures such as CPUs, GPUs, and FPGAs but also mushroomed a class of dedicated hardware AI accelerators specifically designed to accelerate artificial neural networks and machine learning applications.
John McCalpin
OCTOBER 16, 2016
Computer Architecture Computer Hardware Performance cache DRAM high performance computing memory bandwidth memory latency STREAM benchmark“Memory Bandwidth and System Balance in HPC Systems” If you are planning to attend the SuperComputing 2016 conference in Salt Lake City next month, be sure to reserve a spot on your calendar for my talk on Wednesday afternoon (4:15pm-5:00pm).
DZone
SEPTEMBER 29, 2021
For example, you can monitor the behavior of your applications, the hardware usage of your server nodes, or even the network traffic between servers. One prominent solution is the open-source tool Nagios which allows you to monitor hardware in every detail. Introduction.
John McCalpin
JANUARY 22, 2018
Hardware performance counter results for a simple benchmark code calling Intel’s optimized DGEMM implementation for this processor (from the Intel MKL library) show that about 20% of the dynamic instruction count consists of instructions that are not packed SIMD operations (i.e., This is an uninspiring fraction of peak performance that would normally suggest significant inefficiencies in either the hardware or software.
DZone
JANUARY 23, 2022
Hardware - servers/storage hardware/software faults such as disk failure, disk full, other hardware failures, servers running out of allocated resources, server software behaving abnormally, intra DC network connectivity issues, etc.
John McCalpin
NOVEMBER 5, 2016
It seems very likely that the hardware has to be able to merge these two load operations into a single L1 Data Cache access to keep the rate of cache accesses from being the performance bottleneck. But 2 32-bit loads is only 1/8 of a natural 512-bit cache access, and it seems unlikely that the hardware can merge cache accesses across multiple cycles. Algorithms Computer Architecture Computer Hardware Performance arithmetic high performance computing microprocessors
John McCalpin
DECEMBER 6, 2016
Cache Coherence Implementations Computer Architecture Computer Hardware Performance memory bandwidth memory latency Xeon PhiThe Xeon Phi x200 (Knights Landing) has a lot of modes of operation (selected at boot time), and the latency and bandwidth characteristics are slightly different for each mode.
DZone
FEBRUARY 8, 2022
But what is the metric that shows service hardware monopolization by a group of users? Scenario. Any service provider tries to reach several metrics in their activity. One group of these metrics is service quality. Quality metrics contain: The ratio of successfully processed requests.
High Scalability
APRIL 8, 2019
Hardware infrastructure. This is a guest post by Hugues Alary , Lead Engineer at Betabrand , a retail clothing company and crowdfunding platform, based in San Francisco. This article was originally published here. Early infrastructure. Rackspace. The scalability and maintainability issue. Scaling development processes. The advent of Docker. Kubernetes. Learning Kubernetes. Officially migrating. The development/staging environments. A year after. kubernetes
Sutter's Mill
APRIL 23, 2012
Now welcome to the hardware jungle. Concurrency Hardware Software Development Talks & Events WebLast month in Kansas City I gave a talk on “Welcome to the Jungle,” based on my recent essay of the same name (sequel to “The Free Lunch Is Over”) concerning the turn to mainstream heterogeneous distributed computing and the end of Moore’s Law.
Sutter's Mill
APRIL 6, 2011
We know that getting full computational performance out of most machines—nearly all desktops and laptops, most game consoles, and the newest smartphones—already means harnessing local parallel hardware, mainly in the form of multicore CPU processing. You can expect the above keynote to be, well, keynote-y… oriented toward software product features and of course AMD’s hardware, with plenty of forward-looking industry vision style material.
Sutter's Mill
DECEMBER 29, 2011
Now welcome to the hardware jungle. For the first time in the history of computing, mainstream hardware is no longer a single-processor von Neumann machine, and never will be again. Concurrency Hardware Opinion & Editorial Software DevelopmentWith so much happening in the computing world, now seemed like the right time to write “Welcome to the Jungle” – a sequel to my earlier “The Free Lunch Is Over” essay. Here’s the introduction: Welcome to the Jungle.
Addy Osmani
DECEMBER 29, 2019
Adaptive Loading is a pattern for delivering a fast core experience to all users (including low-end devices) where you progressively add high-end-only features, if a user's network and hardware can handle it
Sutter's Mill
MAY 28, 2012
Mainstream hardware – many kinds of parallelism: What’s the relationship among multi-core CPUs, hardware threads , SIMD vector units (Intel SSE and AVX , ARM Neon ), and GPGPU (general-purpose computation on GPUs, which I covered at C++ and Beyond 2011 )? Task and data parallelism: What’s the difference between task parallelism and data parallelism, which kind of of hardware does each allow you to exploit, and why?
Sutter's Mill
JUNE 16, 2011
Portable: It allows shipping a single EXE that can use any combination of GPU vendors’ hardware. The initial implementation uses DirectCompute and supports all devices that are DX11 capable; DirectCompute is just an implementation detail of the first release, and the model can (and I expect will) be implemented to directly talk to any interesting hardware. More to come… C++ Concurrency Hardware Microsoft Software Development Talks & Events
High Scalability
APRIL 30, 2021
This channel is the perfect blend of programming, hardware, engineering, and crazy. Hey, HighScalability is back! After watching you’ll feel inadequate, but in an entertained sort of way. Love this Stuff? I need your support on Patreon to keep this stuff going.
Alex Russell
MARCH 6, 2021
Hardware Past As Performance Prologue. Regardless, the overall story for hardware progress remains grim, particularly when we recall how long device replacement cycles are: Tap for a larger version.
DZone
AUGUST 31, 2020
The very flexible nature of the technology opens many doors, including business collaborations, reuse in third-party products, or even conquering hardware barriers by reaching a spectrum of devices. Introduction. APIs — the current “big thing” — offer the opportunity for modern organizations to unlock new and lucrative business models. The article below covers some tips on how to spin the API flywheel and leverage its possibilities.
Sutter's Mill
JUNE 21, 2012
Now welcome to the hardware jungle. Cloud Concurrency Hardware Software Development Talks & EventsWhile visiting Facebook earlier this month, I gave a shorter version of my “Welcome to the Jungle” talk, based on the eponymous WttJ article. They made a nice recording and it’s now available online here: Facebook Engineering. Title: Herb Sutter: Welcome to the Jungle.
DZone
APRIL 26, 2022
The underlying SIMD hardware is exposed via instructions such as SSE, AVX, AVX2, AVX-512, and those in the Intel® Xe Architecture Gen12 ISA. Introduction. Modern CPU and GPU cores use single instruction, multiple data (SIMD) execution units to achieve higher performance and power efficiency.
Testlodge
APRIL 14, 2021
These systems are a combination of different hardware and software which have been configured to perform the desired task. Configuration testing is performed to discover the optimum combinations of software and hardware specifications that allow the system to work without flaws.
DZone
JULY 23, 2021
The fail-over condition arises due to uncontrolled network failure, OS failure, hardware failure or DR drill. Reducing time for disaster recovery is crucial for organizations needing to achieve operational resiliency.
130 
Let's personalize your content