Weiser Security Application: Fill & Download for Free

You probably aren’t going to like this answer, but it’s because civilian firearm ownership is very heavily restricted. Yes, guns are a common sight, but they’re almost always carried by people doing regular or reserve military or border police service, who are often out and about, and sometimes in civilian clothes. Settlers in the West Bank are issued weapons for self-defense, but those are property of the army and can be confiscated at will. For an ordinary citizen, it’s almost impossible to get a gun. You need to have a gun license, and it’s typically very hard to get one. You need to be a retired military, police, or prison guard officer above a certain rank, a security guard (who by law can carry guns outside of work hours), or have a genuine reason such as hunting, animal control, or a provable threat to yourself that would justify a gun in self defense (such as if you work in an occupation where you might need it, like a jeweler) . A lot of gun license applications are rejected, and even if you get a gun, you have to periodically renew your license, so you’ll have to re-take shooting courses and psychological tests every few years. If you managed to get a gun license for self-defense reasons, aside from bullets you use on a firing range you’re only allowed to buy 50 bullets a year. Oh, and once you own a gun, the government puts your name on a list of everyone who has a gun license.That’s why school shootings, along with gun crime in general, are very low in Israel. Outside national service, most people do not have guns.

One of Israel’s main ways of preventing gun violence is something that Americans would not want to adopt. Gun control. Israel has very strict gun control laws. Ordinary citizens need to get a gun license to own one, and it’s almost impossible to get one. Without demonstrating a genuine reason, you won’t get one, and the rate of rejection of gun license applications is very high. Even if you do get one, there are more hoops to jump through. You need to pass a criminal background, health, and mental health check and pass a weapons-training course. You then need to pass a shooting course every three years and a psychological test every six years to keep your gun license.However, in public venues in Israel, there is heavy security. And it’s everywhere. If you want to enter a bus terminal, train station, shopping mall, or university campus, you have to go to through airport-style security. This means things like putting your bags through x-ray machines or having a guard open them and look into them, and walking through scanners.

This question takes me back many years.As others have noted, the question should state: “In C++, you have to manually do your own memory management.” Manual memory management is not generally considered a form of automatic garbage collection, but I still understood the question.During the 1990’s when the CPU wars were well underway, I took an intense interest in high-level programming languages, especially languages that could exploit the new capabilities of modern system processors. That was also still in the heyday of RISC [1]designs, when it looked like modern RISC processors from Digital, Sun, IBM and others would outperform conventional designs from companies like Intel.Early in the 1990’s I used C/C++ extensively, and learned much of the code base behind the GNU Compiler Collection (GCC[2]). By the mid-1990’s an interesting toy language emerged from Sun, named “Java[3]”.Except Java was perhaps no toy. It included portable APIs for multithreading and networking, which interested me at the time for the development of high-performance server applications, and had a bytecode compiler and a portable virtual machine with garbage collection built in. A bytecode interpreter was doomed to always be slow in early languages, but just-in-time compilers (JIT) quickly emerged to translate Java bytecode into machine code at runtime. Finally we had a portable high-level language that looked like it had a chance to rival C/C++ in application perrformance.And early results with simple algorithms were promising. With a quality JIT compiler, Java benchmarks were doing well. Some proponents at Sun and elsewhere even claimed Java would outperform traditional compiled languages like C and C++. The reasoning sounded good—the application code did not need to execute synchronous instructions to handle the details of freeing memory allocations, leading to shorter code paths, and the tasks of reclaiming memory could even be handled asynchronously on systems with symmetric multi-processing (SMP). Plus, a JIT compiler could optimize code with the benefit of runtime profiling information that wouldn’t be available in static code compilation.If it sounds too good to be true, it probably is.Here’s the thing. Language designers in the 1990’s had good ideas. So did hardware designers. I just don’t think they talked to each other at all.CPU performance was hitting the “memory wall[4]”. Faster clock cycles and superscalar architectures were no longer yielding the promised benefits. What good is a processor that can execute 4 instructions per clock cycle if it repeatedly stalls waiting for main memory? The theory behind RISC design was to simplify the instruction set, yielding more silicon that could be devoted to other purposes, like a fast memory cache. Some processor models implemented two levels of cache, some (like the 64-bit Digital Alpha) had 3.So a principle called locality of reference became commonplace. Main memory was slow to access, stalling processor performance. Cache memory was fast, but cache sizes were small. It became imperative to design languages that would improve spatial locality (tending to access memory areas that are adjacent or close) and temporal locality (accessing same locations repeatedly in a short time frame) to achieve the best cache hit ratios.Stack-based languages tended to be ideal for this. C and C++, when using local variables rather than heap, tended to exhibit good spatial and temporal locality. Heap allocation was harder, and languages with automatic garbage collection tended to be the worst.A mark-sweep collector design scans through the memory heap on each major collection to find unused regions that can be freed. This process alone is memory intensive, and therefore slow, and tends to blow out the processor cache with misses because it has to look for everything to perform an accurate collection. And the memory heap itself can become very fragmented.Copying collectors solve the fragmentation problem, but the actual memory copy would again overwrite everything in the processor cache. So a full collection would b slow to execute, and relatively slow to restart from.I tested quite a bit with generational collector designs. In theory, if the generation were small enough to fit in processor cache, I might be able to execute a minor collection entirely (or at least mostly) in cache. In theory, but I could never make it work in practice.My experiments were done mostly on the defunct GNU Compiler for Java (GCJ[5]) project, attached to the Boehm-Demers-Weiser[6] open source collector library. Results were good, but never better than a similar well-designed C/C++ application with manual memory management.And the promised breakthroughs never took place. Java code performed reasonably well on modern architectures, as did C# later on. But never superior to C/C++, or even Fortran. The memory wall has never been solved.With single processors hitting a performance limit due to memory architecture, research started to focus more and more on parallel computation. Early SMP designs supported parallel processing on a single computational node, and low-latency networks supported parallel processing over many nodes. Thus the era of cluster computing was born, and we began to talk about “scale out” designs rather than “scale up”.Since then, processor architecture and language design have seen only incremental improvements. Garbage collection is here to stay, largely because it is far less error prone than manual memory management, and security exploits are harder to find in a language like Java with array-bounds checking and automatic garbage collection. The latter is especially important in the era of the Internet, and along with it, many attempts to exploit vulnerable software.But the many benefits of garbage collection stop short of the theoretical performance advantages, which have never quite been realized in practice. And that’s true for games or any other application that calls for high throughput and/or real-time performance.Footnotes[1] Reduced instruction set computer - Wikipedia[2] GCC, the GNU Compiler Collection[3] OpenJDK[4] Random-access memory - Wikipedia[5] GCJ - GCC Wiki[6] https://www.hboehm.info/gc/