Hans-Juergen Boehm
Hans Boehm joined Google as a software engineer in the Android runtime group in 2014. Before that he held various positions at the University of Washington, Rice University, Xerox PARC, SGI (on the same campus as now), and most recently as research manager at HP Labs. He is an ACM Fellow.
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Towards an API for the Real Numbers
ACM, pp. 562-576
Preview abstract
The real numbers are pervasive, both in daily life, and in mathematics.
Students spend much time studying their properties. Yet computers and
programming languages generally provide only an approximation geared
towards performance, at the expense of many of the nice properties we
were taught in high school.
Although this is entirely appropriate for many applications, particularly
those that are sensitive to arithmetic performance in the usual sense,
we argue that there are others, where it is a poor choice. If arithmetic
computations and result are directly exposed to human users who are
not floating point experts, floating point approximations tend to be
viewed as bugs. For applications such as calculators,
spreadsheets, and various verification tasks, the cost of
precision sacrifices are high, and the performance benefit is often not
critical. We argue that although previous attempts to provide accurate
and understandable results for such applications using the recursive
reals, were great steps in the right direction, they do not suffice.
Comparing such numbers diverges if they are equal. But in many cases
we cannot produce results expected by users without resolving
equality of numbers. We propose an API for such a real number type,
describe a detailed, and surprisingly compact and simple implementation, and
demonstrate its utility. The approach relies heavily on classical number theory
results.
The resulting arithmetic, which takes advantage of these partial decision procedures,
is used in a calculator application with more than 100 million users.
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Small-data computing: Correct calculator arithmetic
Communications of the ACM (CACM Vol. 60 No. 8, August 2017), 60(2017), pp. 44-49
Preview abstract
Calculators conventionally use some flavor of fixed precision floating point arithmetic. The bundled Android 6.0 Marshmallow calculator instead uses demand-drive evaluation or “constructive real” arithmetic to guarantee fully accurate results. We explain why this matters, the opportunities it creates, and the challenges in incorporating constructive real arithmetic in a tool aimed at a very broad audience.
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Preview abstract
Byte addressable non-volatile memory (NVRAM) is likely to
supplement, and perhaps eventually replace, DRAM. Applications
can then persist data structures directly in memory
instead of serializing them and storing them onto a
durable block device. However, failures during execution
can leave data structures in NVRAM unreachable or corrupt. In
this paper, we address memory management of non-volatile
memory, offering an integrated allocator and garbage collector
that maintains internal consistency, minimizes memory
leaks, and is efficient in the face of failures.
We show that a careful allocator design can both support a
less restrictive and much more familiar programming model.
By lazily persisting non-essential metadata and by employing
a post-failure recovery-time garbage collector, the per
allocation persistence overhead is greatly reduced. Experimental
results show that the resulting online speed and scalability
of our allocator are comparable to well-known transient
allocators and significantly better than state-of-the-art
persistent allocators.
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Outlawing ghosts: avoiding out-of-thin-air results
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Brian Demsky
Workshop on Memory Systems Performance and Correctness (MSPC), ACM, New York, NY(2014)
