بعد از نصب ویندوز کارهای مهمی وجود دارد که باید انجام شوند. از نصب درایورها تا تهیه نسخه پشتیبان برای روز مبادا.
در این آموزش به 5 کار کلیدی میپردازیم که حتما باید انجام گیرد.
Iterative computations are at the core of the vast majority of data-intensive scientific computations. Recent advancements in data intensive computational fields are fueling a dramatic growth in number as well as usage of such data intensive iterative computations. The utility computing model introduced by cloud computing combined with the rich set of cloud infrastructure services offers a very viable environment for the scientists to perform data intensive computations. However, clouds by nature offer unique reliability and sustained performance challenges to large scale distributed computations necessitating computation frameworks specifically tailored for cloud characteristics to harness the power of clouds easily and effectively. My research focuses on identifying and developing user-friendly distributed parallel computation frameworks to facilitate the optimized efficient execution of iterative as well as non-iterative data-intensive computations in cloud environments, alongside the evaluation of heterogeneous cloud resources offering GPGPU resources in addition to CPU resources, for data-intensive iterative computations.
Abstract—Composing a scientific workflow from scratch may be time-consuming, even if the scientist is fully aware of the semantics, the inputs, and the outputs of the expected workflow.
Reusing existing services and parts from already composed workflows can aid in reducing the total workflow composition time. However, matching the semantics and the inputs and outputs of these reusable components manually is not an easy task, especially when there are hundreds of such components available. Even components are annotated with information on the semantics of their inputs and outputs, the complex nature of the semantic languages may make manual component selection even harder. In this paper, we propose a Case-Based Reasoning (CBR) approach to assist composition of workflows based on the characteristics of the inputs and the outputs of the reusable workflow components, facilitating user exploitation of existing services and workflows during workflow composition. The architecture can also be extended to utilize the semantics of the various components improving the precision of the identified reusable components.
Parallel programming: how new language features helpMehran Davoudi
In these presentation I talk about Parallel Programming, its necessities, challenges.
Then I talk about how the syntax of languages like C# advances to improve the expressiveness of parallel programming.
بعد از نصب ویندوز کارهای مهمی وجود دارد که باید انجام شوند. از نصب درایورها تا تهیه نسخه پشتیبان برای روز مبادا.
در این آموزش به 5 کار کلیدی میپردازیم که حتما باید انجام گیرد.
Iterative computations are at the core of the vast majority of data-intensive scientific computations. Recent advancements in data intensive computational fields are fueling a dramatic growth in number as well as usage of such data intensive iterative computations. The utility computing model introduced by cloud computing combined with the rich set of cloud infrastructure services offers a very viable environment for the scientists to perform data intensive computations. However, clouds by nature offer unique reliability and sustained performance challenges to large scale distributed computations necessitating computation frameworks specifically tailored for cloud characteristics to harness the power of clouds easily and effectively. My research focuses on identifying and developing user-friendly distributed parallel computation frameworks to facilitate the optimized efficient execution of iterative as well as non-iterative data-intensive computations in cloud environments, alongside the evaluation of heterogeneous cloud resources offering GPGPU resources in addition to CPU resources, for data-intensive iterative computations.
Abstract—Composing a scientific workflow from scratch may be time-consuming, even if the scientist is fully aware of the semantics, the inputs, and the outputs of the expected workflow.
Reusing existing services and parts from already composed workflows can aid in reducing the total workflow composition time. However, matching the semantics and the inputs and outputs of these reusable components manually is not an easy task, especially when there are hundreds of such components available. Even components are annotated with information on the semantics of their inputs and outputs, the complex nature of the semantic languages may make manual component selection even harder. In this paper, we propose a Case-Based Reasoning (CBR) approach to assist composition of workflows based on the characteristics of the inputs and the outputs of the reusable workflow components, facilitating user exploitation of existing services and workflows during workflow composition. The architecture can also be extended to utilize the semantics of the various components improving the precision of the identified reusable components.
Parallel programming: how new language features helpMehran Davoudi
In these presentation I talk about Parallel Programming, its necessities, challenges.
Then I talk about how the syntax of languages like C# advances to improve the expressiveness of parallel programming.
در این کتاب چه میخوانیم :
• ضرورت استفاده از Siem و بخش soc , noc
• بررسی عنوان IDS و IPS ها
• معماری ossec
• معماری wazuh
• نصب ossec
• نحوه مهاجرت از ossec به Wazuh
• نصب آفلاین wazuh
• ویژگیهای wazuh و امکانات آن
در این کتاب چه میخوانیم :
• ضرورت استفاده از Siem و بخش soc , noc
• بررسی عنوان IDS و IPS ها
• معماری ossec
• معماری wazuh
• نصب ossec
• نحوه مهاجرت از ossec به Wazuh
• نصب آفلاین wazuh
• ویژگیهای wazuh و امکانات آن