[Kitploit] AWSGen.py - Generates Permutations, Alterations And Mutations Of AWS S3 Buckets Names

AWSGen.py - Generates Permutations, Alterations And Mutations Of AWS S3 Buckets Names

PUBG Mobile 0.12.0 Update

What's next after PUBG mobile 0.11.5 update? Yeah, it's 0.12.0 update! This update will also bring some new guns, new features, new attachments, and many new features. So let us have a look at those features.

1. MP5K (Gun) :

           MP5K is a new SMG gun coming to PUBG mobile 0.12.0 update. This gun will be available only on Vikendi map and will replace Vector from Vikendi map. This gun will require 9mm ammo. The MP5K is highly versatile with single, burst and full auto firing options. It can support all attachment types. View the video to know more about it.

MP5K 

2. Skorpion (Gun) :

          It is a full-auto weapon pistol that works on 9mm ammo. Its capacity can be increased from default 20 rounds to 40 rounds using a standard extended magazine. It can be switched from single fire to full auto. The only disadvantage is that it has lower per bullet damage than other pistols. If you want to use this weapon, you have to wait for PUBG mobile 0.12.0 update.

Skorpion

3. Competitive mode will be re-added:

         This mode was once available in PUBG but later it was removed. Now on public demand, they are bringing it back on PUBG mobile 0.12.0 update. Those players who don't know what it is or recently started players, let me explain it to you. So basically, it is an arcade mode where there are no bots i.e. all the players are real. 
         The minus point of this mode is that it takes 10 minutes or more, depending on the number of players, to load. This mode is perfect for those who hate bots or for pro players who want only real players to kill.

Competitive mode

4. Canted sight (attachment) :

        It is a secondary attachment that allows the player to quickly switch between the 1x Canted sight and the other scope used. It is already launched in PUBG PC, Xbox and PS4. To know more about Canted sight you can visit my post about it. 
                 It was planned to release in PUBG 0.11.5 update but later it was postponed to PUBG mobile 0.12.0 update. 

Canted Sight

5. Death Cam (feature) :

          Death Cam is a new feature coming to PUBG mobile   0.12.0 update. If you are playing the game and suddenly someone kills you then this Cam will allow you to view the scene i.e. after your death you can use the feature to know exactly who killed you, what gun the opponent used and other information. The main reason behind the adding of this feature is that many players were reporting the presence of hackers in the game. So PUBG added this feature to know whether there was a real hacker or not.

Death Cam

6. Bug tracking system :

       Lagging is the worst enemy for online players. PUBG Corp. understands it and is trying its best to remove lagging as much as possible. 
    For this, PUBG is installing a software called Bug tracking system. This software will scan the game, detect any bug present in the game and will report it to the PUBG developers. The PUBG developers can, then work on that bug and remove it. This is just a concept for now but we hope to find it in the PUBG mobile 0.12.0 update.
  
7. More chats are added : 

    If you are bored with existing chats like "Help!", " I got supplies!" etc. then in the PUBG mobile 0.12.0 update you will be able to add some more chats in both male and female voices. And you can irritate your friends as like I do with my friends. 

Chats in PUBG

8. The White Eagle : 

       You will be able to have the White Eagle as your companion in the PUBG mobile 0.12.0 update. The Eagle will follow wherever you go. 

The White Eagle

9. Scope colors :

       The PUBG mobile 0.12.0 update will let you change the color and shape of the pointer of a gun. People who were bored red color can change it to several colors including white, sky, pink, black and others.

Scope colors

Release date:

        There is no officially confirmed release date for PUBG mobile 0.12.0 update, but the expected date, as of my prediction, is 20-25 April 2019. I repeat again this is my prediction and not officially confirmed. Once the date is officially confirmed, the date will be posted on our facebook page. So please like our page to get future updates.

Enough reading! Now it's your time to tell me your opinion about these updates. The comment section is below.

New Year, Fist Update....

Hello all,

 

Just wanted to drop in and give an update. The transition from WGF is complete, we have our warehouse and have been shipping from that location for about two months. We have worked out the software issues for the wholesale orders and have been filling them.

 

We have about a year's supply of product on hand and OOS items such as the Panzerjäger are on the water heading here now.

 

I have been working on the day to day business aspects, cost analysis, product restocks back end implementation issues, etc. so not a lot of glamorous items to give an updated on for that front.

 

We have two restock orders incoming from China, the cost has been educational. The cost of shipping is not just crazy expensive for my customers but for us as well. In some cases, it costs more to ship a product than it does to produce it, in other cases the cost to produce a kit was not in line with what it is being sold at into distribution. Some kits were being sold at a net loss once shipping was factored in. Unfortunately, this will mean a price increase, some kits will see a marginal increase, other will be a bit more drastic.

I will give a detailed SKU by SKU run down and explanation later this week.

 

We have two new SKU's that will be offered once they arrive. The 15mm scale Capacitor cooler and a 60mm tall display model of one of our Assault Troopers. We should have these in hand sometime next month. We are putting the final touches on the files for the Shadokesh main trooper box set. No eta on a release date yet for the Shadokesh, until they are on the water and heading here it is simply impractical to give an estimate.

 

That's it for now.

All the best!

Mark

Worst Or Useless Things In PUBG

While playing PUBG weapons, items and many kinds of equipment are required. Most of the items are useful and play an important role in getting a 'Winner winner chicken dinner'. But there are some useless items as well. We have given 8 useless/ worst items of PUBG as follows : 

1. Clothes : 

                         Clothes in PUBG are actually only meant for impressive outlook. Except for helmet and vests the other clothes have nothing with your win/ lose.  

2. Vans : 

                     PUBG has plenty of vehicles throughout the many different maps. Van, I consider, is the most useless vehicle. Because of its big size, its speed and vulnerability are limited. And no one would want to be slow in PUBG.

3. Quickdraw magazine : 

     

                 Being able to reload faster is the only good thing about the quickdraw magazine. But most of the other attachments have multiple different uses and a lot of them are better than being able to reload faster.

4. Gas Can : 

       

                    If you have a vehicle that is useful to your match then take a gas can. Or just leave it as it is basically useless.

5. Used vests and helmets : 

                    An unused vest or helmet can last longer than a used one. It is also less effective. Neglect any used vests/helmet unless you absolutely need them.

6. Shotgun chokes : 

                  Due to the increased range, the weapon's damage starts to degrade as the bullets are in flight. If you have multiple targets, the choke may not work as well as the shotgun without chokes should.

7. R1895 Pistol : 

              The worst pistol in PUBG is the R1895.
Putting a scope in it is not available. Also, it takes a longer time to reload than many other pistols. So avoiding it is better. 

8. Bullet Loops : 

               The worst thing about them is that they decrease the base spread of a weapon. There are better and more useful attachments that have a variety of indispensable skills.

If you enjoyed, comment in the below and let us know. Also, do share the link
https://sudragamer.blogspot.com/?m=1
and follow us for interesting updates on PUBG.

Frankenstein: A New Version Of It's Alive From Invedars

Hey guys. News about the game formerly known as It's Alive.

After the first prototypes, two editions of It's Alive from Reiver Games, and two versions of Hanukkah themed versions called Candle Quest by Victory Point Games and on The Game Crafter (still available), the game has been picked up by Invedars, returning to its original Frankenstein theme.

The new version is called Frankenstein and it looks amazing. New artwork, and a figurine and a new events expansion for Kickstarter backers.

The project is up on Kickstarter and reached its goal in only 24 hours. It is now many times above its goal.

They have already sent prototypes to reviewers for new reviews, for example:

Follow Invedars and progress about the game on Facebook.

Tech Book Face Off: Programming Massively Parallel Processors Vs. Professional CUDA C Programming

After getting an introduction to GPU programming with CUDA by Example, I wanted to dig in deeper and get to know the real ins and outs of CUDA programming. That desire quickly lead to the selection of books for this Tech Book Face Off. The first book is definitely geared to be a college textbook, and as I spent years learning from books like this, I felt comfortable taking a look at Programming Massively Parallel Processors: A Hands-on Approach by David B. Kirk and Wen-mei W. Hwu. The second book is targeted more at the working professional, as the title suggests: Professional CUDA C Programming by John Cheng, Max Grossman, and Ty McKercher. I was surprised by both books, and not in the same way. Let's see how they do at teaching CUDA programming.

VS.

Programming Massively Parallel Processors

The polite way to critique this book is to say, it's somewhat verbose and repetitive, but if you can get past that, it has a lot to offer in the way of example CUDA programs that show how to optimize code for the GPU architecture. A slightly less polite way to say that would be that while this book does offer some good code examples, the writing leaves much to be desired, and much better books are out there that cover the same material. The honest assessment is that this book is just a mess. Half the book could be cut and the other half rewritten to better explain things with clearer, non-circular definitions. The only good thing about the book is the code examples, and many of those examples are also redundant, filling the pages of the book with lines of code that the reader has seen multiple times before. This book could have been a third the length and covered the same amount of material.

Even though that last bit was a pretty harsh review, we should still explore what's in the book, if only to see how the breadth of material compares to Professional CUDA C Programming. The first chapter is the normal introduction to the book's material, describing the architecture of a GPU and discussing how parallel programming with this architecture is so different than programming on a CPU. The verbosity of this chapter alone should have been a clue that this book would drag on and on, but I was willing to give it a chance. The next chapter introduces our first real CUDA program with a vector addition kernel. We're still getting started with CUDA C at this point, so I chalk up the authors' overly detailed explanations to taking extra care with novice readers. We end up walking through all of the parts of a working CUDA program, explaining everything in excruciating detail.

The third chapter covers how to work more efficiently with threads and loading data into GPU memory from the CPU with a more complex example of calculating image blur. We also get our first exposure to thread synchronization, something that must be thoroughly understood to program GPUs effectively. This chapter is also where I start to realize how nutty some of the explanations are getting. Here's just one example of them describing how arrays are laid out in memory:

A two-dimensional array can be linearized in at least two ways. One way is to place all elements of the same row into consecutive locations. The rows are then placed one after another into the memory space. This arrangement, called row-major layout, is depicted in Fig. 3.3. To improve readability, we will use M_j,i to denote the M element at the jth row and the ith column. P_j,i is equivalent to the C expression M[j][i] but is slightly more readable. Fig. 3.3 illustrates how a 4×4 matrix M is linearized into a 16-element one-dimensional array, with all elements of row 0 first, followed by the four elements of row 1, and so on. Therefore, the one-dimensional equivalent index for M in row j and column i is j*4 +i. The j*4 term skips all elements of the rows before row j. The i term then selects the right element within the section for row j. The one-dimensional index for M_2,1 is 2*4 +1 =9, as shown in Fig. 3.3, where M₉ is the one-dimensional equivalent to M_2,1. This process shows the way C compilers linearize two-dimensional arrays.

Wow. I'm not sure how a reader that needs this level of detail for understanding how a matrix is arranged in memory is going to understand the memory hierarchy and synchronization issues of GPU programming. This explanation is just too much for a book like this. Readers should already have some knowledge of standard C programming, including multi-dimensional array memory layout, before attempting CUDA programming. I can't imagine learning both at the same time going very well. As for readers who already know how all of this stuff works, they could easily skip every other paragraph and skim the rest to make trudging through these explanations more tolerable.

The next chapter is on how to manage memory and arrange data access to optimize memory usage and bandwidth. We find that memory management is just as, if not more important than thread management for making optimal use of the GPU computing resources, and the book solidifies this understanding through an extended optimization example of a matrix multiplication kernel.

At this point we've learned the fundamentals of GPU programming, so the next chapter moves into more advanced topics in performance optimization with the memory hierarchy and the compute core architecture. Then, chapter six covers number format considerations between integers and single- and double-precision floating point representations. The authors' definition of representable numbers struck me as exceptionally cringe-worthy here:

The representable numbers of a representation format are the numbers that can be exactly represented in the format.

This is but one example of their impenetrable and useless definitions. More often than not, I found that if I hadn't already known what they were talking about, their discussions would provide no further illumination.

Now we get into the halfway decent part of the book, the extended example chapters on parallel patterns. Each of these chapters works through a different example kernel of a particular problem that comes up often in parallel programming, and they introduce additional features of GPU programming that can assist in solving these problems in a more optimal way. The contents of these chapters are as follows:

• Chapter 7: Convolution
• Chapter 8: Prefix Sum (Accumulator)
• Chapter 9: Parallel Histogram Calculation
• Chapter 10: Sparse Matrix Computation
• Chapter 11: Merge Sort
• Chapter 12: Graph Search

As long as you skim the descriptions of the problems and solutions, and focus on understanding the code yourself, these chapters are quite useful examples of how to write performant parallel programs with CUDA. However, the authors continue to suffer from what seems to be a mis-interpretation of the phrase, "a picture is worth a thousand words." For every diagram they use, they also include a thousand words or more of explanation, describing the diagrams ad nauseam. 

The next chapter covers how to kick off kernels from within other kernels in order to enable dynamic parallelism. Up until this point, all kernels have been launched from the host (CPU) code, but it is possible to have kernels launch other kernels to take advantage of additional parallelism while the code is executing on the GPU, an effective feature for some algorithms. Then, the next three chapters are fairly useful application case studies. Like the parallel pattern example chapters, these chapters use CUDA code to show how to take advantage of more advanced features of the GPU, and how to put together everything we've learned so far to optimize some example parallel programs. The applications described are for non-Cartesian MRI, molecular visualization and analysis, and machine learning neural networks, so nice, interesting topics for GPU programming.

The last five chapters were either more drudgery or topics I wasn't interested in, so I skipped them and called it quits for this long and tedious book. For completeness, those chapters are on how to think when parallel programming (so a pep talk on what to think about from authors that couldn't clearly describe much else in the book), multi-GPU programming, OpenACC (another GPU programming framework, like CUDA), still more performance considerations, and a summary chapter. 

I couldn't bring myself to keep reading chapters that wouldn't amount to anything, so I put down the book after finishing the last chapter on application case studies. I found that chapters seven through sixteen contained most of the useful information in the book, but the introduction to CUDA programming was too verbose and confusing. There are much better books out there for learning that part of CUDA programming. Case in point: CUDA by Example or the next book in this review.

Professional CUDA C Programming

Unlike the last book, I was surprised by how readable this book was. The authors did an excellent job of presenting concepts in CUDA programming in a clear, direct, and succinct manner. They also did this without resorting to humor, which can sometimes work if the author is an excellent writer, but it often feels forced and lame when done poorly. It's better to stick to clear descriptions and tight writing, as these authors did quite well. I was actually disappointed that I didn't read this book first, instead saving it until last, because it did the best job of explaining all of the CUDA programming concepts while covering essentially the same material as Programming Massively Parallel Processors and certainly more than CUDA by Example. 

The first chapter is the obligatory introduction to CUDA with the requisite Hello, World program showing how to run code on the GPU. Right away, we can see how well-written the descriptions are with this discussion of how parallel programming is different than sequential programming:

When implementing a sequential algorithm, you may not need to understand the details of the computer architecture to write a correct program. However, when implementing algorithms for multicore machines, it is much more important for programmers to be aware of the characteristics of the underlying computer architecture. Writing both correct and efficient parallel programs requires a fundamental knowledge of multicore architectures.

We need to be prepared to think differently about problems when parallel programming, and we're going to have to learn the architecture of the underlying hardware to make full use of it. That leads us right into chapter 2, where we learn about the CUDA programming model and how to organize threads on the device, but it doesn't end there. Throughout the book we're learning more and more about the nVidia GPU architecture (specifically the older Fermi and Kepler architectures, since those were available at the time of the book's writing) in order to take full advantage of its compute power. I like how the authors grounded their discussions in specific GPU architectures and showed how the architecture was evolving from one generation to the next. I'm sure the newer Pascal, Volta, and Turing architectures provide more advanced and flexible features, but the book builds a great foundation. Chapter 2 also contains the clearest definition of a kernel that I've seen, yet:

A kernel function is the code to be executed on the device side. In a kernel function, you define the computation for a single thread, and the data access for that thread. When the kernel is called, many different CUDA threads perform the same computation in parallel.

This explanation is the essence of the paradigm shift from sequential to parallel programming, and it's important to understand the effect it has on the code that you write and how it runs on the hardware. In addition to the excellent writing, each chapter has some nice exercises at the end. That's not normally something you find in programming books like this. Exercises seem to be left to textbooks, like Programming Massively Parallel Processors, which had them as well, but in Professional CUDA C Programming they're more well-conceived and more relevant.

The next chapter covers the CUDA execution model, or how the code runs on the real hardware. Here is where we learn how to optimize CUDA programs to take advantage of all of those independent compute cores on the GPU, and this chapter even gets into dynamic parallelism earlier in the book rather than waiting and treating it as a special topic like the last book did.

Chapter 4 covers global memory and chapter 5 looks at shared and constant memory. Understanding the trade-offs of each of these memories is important to getting the maximum performance out of the GPU because most often these programs are memory-bound, not compute-bound. Like everything else, the authors do an excellent job explaining the memory hierarchy and how those trade-offs affect CUDA programs. The examples used throughout the book are simple so that the reader doesn't get bogged down trying to understand unrelated algorithm details. The more complex examples may be thought-provoking, but simple examples do a good job of showcasing the specifics of the topic at hand.

Chapter 6 addresses streams and events, which are used to overlap computation with data transfer. Using streams can partially, or in some cases completely hide the time it takes to get the data into the GPU memory. Chapter 7 explains more optimization techniques by using CUDA instruction-level primitives to directly control how computations are performed on the GPU. These instructions trade some accuracy for speed, and they should be used only if the accuracy is not critical to the application. The authors do a good job of explaining all of the implications here.

The last three chapters weren't as interesting to me, not because I was tired of the book this time, but because they were about the same topics that I skipped in the other CUDA books: OpenACC, multi-GPU programming, and the CUDA development process. The rest of the book was excellent, and far better than the other two CUDA books I read. The writing is clear with plenty of diagrams for better understanding of each topic, and the book organization is done well. If you're interested in GPU programming and want to read one book, this one is it.


Between these two CUDA books, the choice is obvious. Programming Massively Parallel Processors was a bloated dud. It may be worth it just for the large set of example programs it contains, but there are other options coming down the pipeline for that kind of cookbook that may be better. Professional CUDA C Programming was better in every way, and really the book to get for learning CUDA programming. The authors did a great job of explaining complex topics in GPU architecture with concise, understandable writing, relevant diagrams, and appropriate exercises for practice. It's exactly the kind of book I want for learning a new programming language, or in this case, programming paradigm. If you're at all interested in CUDA programming, it's worth checking out.

Conversion Therapist, Short Film, Review

Conversion Therapist is a short film that packs a lot of punch. And it will strike you right in solar plexus, knocking the air out of you. Bears Rebecca Fonté takes on a topic out of the headlines and brings to light what is really being considered behind the niceties of titles used to describe what is happening.

This is a film needing to be watched by every adult to get a better understanding of what is happening. Remember it is brutal, because, yes, it is brutal what has been happening to people.

I saw Conversion Therapist at the 2019 FilmQuest film festival (website).It was nominated for Best Horror Short, Best Actress (Sara Fletcher), and Best Supporting Actor (Michael Dickson).

Synopsis: A pansexual, polyamorous trio kidnap a 'pray-the-gay-away' evangelical conversion therapist and torture him until he sees the light.

This is part of the inspiration for making Conversion Therapist.

This very passionate film was the outlet for Bears to come out as trans to their friends and family. After the shootings at Pulse nightclub in Orlando, Bears was determined to be true to their self and take to the front lines in their own medium, film. Conversion Therapist follows a pansexual, polyamorous trio as they set out to kidnap and convert a 'pray-the-gay-away' preacher, using some of the same methods he used on queer youth, and some that are maybe a little more extreme.

Director Statement

On June 12th, 2016, I woke up to coverage of the Pulse nightclub shooting and felt my heart being ripped out. Even worse, I was due to moderate a Q&A of the Sandy Hook shooting documentary Newtown that night. What world were we living in? In the aftermath of Pulse, I couldn't believe the bigotry of certain "ministers" who did more than hint that they believed the terrorist had done the world a favor. I poured my anger into this script and project.

But I also had started a ticking clock. I realized that I wasn't going to be able to bring this story, with its transgender character, into the world and honestly discuss the story with the actors, crew and audiences without first being honest about myself. When I launched our Kickstarter campaign, I also announced to the world that I was Transgender.

A filmmaker has to realize they are on the front line at festivals, represent these issues as they represent their film, understand what is "in play" with their film and be ready to defend it. For my film, in addition to conversion therapy, I know the discussion will be about my own journey and the character of Salina, on whom the entire plot hinges. The most important thing about making any film is casting—you can't fix that in post. With Conversation Therapist, this was especially important; I refused to cast a non-trans actress. Films and series like Transamerica, The Danish Girl and Transparent have been great for trans-visibility, but the casting of cisgender actors in these roles has been increasingly offensive to the trans community. Transgender actors should be able to tell their own stories. After a 9-month search, I found my star in Evalyn Jake, a young trans woman from Michigan who had never acted before. She is going to be a star if given the chance.

Filmmaker Bio

Bears Rebecca Fonté is a transgender filmmaker, festival programmer, and journalist. They founded Other Worlds Film Festival after two years as the Director of Programming for Austin Film Festival. They also program midnighters for SF Indiefest and consult on festivals around the country. Their short, ROADSIDE ASSISTANCE, was selected for 70 festivals including Fantasia International Film Festival, Dances With Films, Sci-Fi London and Boston SciFi. Other shorts PRENATAL, THE SECRET KEEPER and SMURF #47 played at a combined 80 festivals. Bears Rebecca was a producer on Sundance Jury-Award Winning short THE PROCEDURE and the documentaries CLOSER THAN WE THINK and ARTIST DEPICTION. Their feature thriller iCRIME, which they wrote and directed, was released on DVD by Breaking Glass in 2011. Bears Rebecca serves on the board of the All Genders, Lifestyles, and Identities Film Festival (aGLIFF) in Austin and represents District 6 on the Austin Arts Commission.

You can find out more about Conversion Therapist on IMDb (link).

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