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This section will show how to make concurrent JS as fast as serial JS in many of the most important cases by simply extending optimizations that JavaScriptCore already uses.

JSC optimizes the code for heap accesses using inline caching . We use inline caches for accesses to named properties (like o.f ) and for array accesses (like a[i] ).

Objects that have the same properties at the same offsets will usually share the same structure , which is identified by 32 bits in the object’s type header. If a property access tends to see the same structure, then we will generate new machine code for this property access, which checks that the object has the expected structure and then accesses the property directly. Failed speculation causes recompilation of the inline cache. If the inline cache remains stable (doesn’t recompile much) for a long time and the function that contains it becomes eligible for optimized JIT compilation, then the optimizing JIT compiler might express the inline cache’s code directly in its IR, which has two outcomes: the structure check branches to OSR exit if it fails (causing abrupt termination of the optimized code’s execution), and all of the code for the inline cache (the structure check, the memory access, and any other steps) become eligible for low-level optimization by our DFG and B3 JIT compiler pipelines. Our compilers are good at making type-stable JavaScript property accesses perform great.

Array accesses use similar techniques to detect if an object has array elements, and if so, how they are formatted. We support multiple kinds of storage for array elements depending on how they are being used. Inline caches detect what kind of array each array access is accessing, and we then emit code that speculates for that kind of array access.

Another technique we already use is virtual memory. For example, our WebAssembly implementation uses virtual memory tricks to check the bounds of linear memory accesses for free. We can catch page faults using POSIX signal handlers or Mach exceptions. The handler will know the exact machine state at the point of the fault, and has the power to transfer execution to any state it likes. WebAssembly uses this to throw an exception, but we can use it to transfer control flow to slow paths that handle the generic case of a memory access. Essentially, this means that we can save cycles on safety checks if we can express the condition being checked as something that causes the virtual memory system to issue a page fault. Concurrent JS will require a combination of inline caching and virtual memory tricks to make TID and SW checking cheap.

Inline caching means emitting different code for each property access, and then recompiling each property access potentially many times as we learn new information about what this property access may do. Inline caches are able to get incredibly precise information about the behavior of each property access because we always emit a fast path access that can only handle exactly those cases that we have seen so far. We learn new information by recording everything we know about those accesses that failed the fast path. The complete log of failed accesses is then LUBed (least-upper-bounded) together to create a minimal set of s. We can implement optimizations for new kinds of property accesses — such as the ones that have to check TID and SW bits — by considering in what ways a particular access site might be special and so specially optimizable. Below is a list of conditions we may encounter along with the strategy for how inline caches can test this condition and handle it.

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// APA Journals Article Spotlight // Sacrificing Strangers vs. Helping Them
Summaries of recent APA Journals articles

January 10, 2018

Sacrificing Strangers vs. Helping Them: Two Dimensions of Utilitarian Psychology

In order to study how our minds form moral judgments, psychologists often use moral dilemmas based on the now famous philosophical thought experiments involving runaway trolleys. In one such dilemma, people are asked to imagine that a runaway trolley is about to kill five workers but that this can be prevented if one were to push a large person off a footbridge. This person will die, but by blocking the runaway trolley, the lives of the five workers will be saved.

When participants in an experiment judge that we should sacrifice the large person in order to save a greater number, they are usually said to be making a "utilitarian" judgment because they seem to echo the utilitarian idea that our moral decision should only focus on the consequences.

A growing body of research has investigated the processes that lead to such "utilitarian" judgments and the factors that can influence them. A number of studies have suggested that judgments rejecting such sacrifices are based in more emotional processing than judgments endorsing them. More disturbingly, "utilitarian" judgments were found to be associated with anti-social traits such as psychopathy — both at a sub-clinical and clinical level. This result has led MultiWear Wrap Marble Fire Multi wear 2 by VIDA VIDA RmYTsR
to conclude that "goodness has nothing to do" with utilitarianism, and that "utilitarians are not nice people".

But such a tie between utilitarianism and antisocial traits is more than a little surprising when one considers the historical origins and influence of utilitarianism. Developed in 18th century Britain, utilitarianism is a philosophical theory grounded in the core idea that we should always act in the way that would impartially maximize the well-being of everyone on the planet, whether friend or stranger, near or far, human or animal.

This is a simple but revolutionary idea. Utilitarians like Jeremy Bentham, John Stuart Mill, and Peter Singer have played a critical role in "expanding the moral circle" and making morality more inclusive by fighting against sexism, racism, and "speciesism", passionately arguing for political and sexual liberty, and making influential efforts to eradicate poverty in developing countries.

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