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For domain specific languages, "scripting languages", dynamic languages, and for virtual machine-based languages, the most straightforward implementation strategy is to write an interpreter. A simple interpreter consists of a loop that fetches the next bytecode, dispatches to the routine handling that bytecode, then loops. There are many ways to improve upon this simple mechanism, but as long as the execution of the program is driven by a representation of the program other than as a stream of native instructions, there will be some "interpretive overhead".There is a long history of approaches to removing interpretive overhead from programming language implementations. In practice, what often happens is that, once an interpreted language becomes popular, pressure builds to improve performance until eventually a project is undertaken to implement a native Just In Time (JIT) compiler for the language. Implementing a JIT is usually a large effort, affects a significant part of the existing language implementation, and adds a significant amount of code and complexity to the overall code base.In this paper, we present an innovative approach that dynamically removes much of the interpreted overhead from language implementations, with minimal instrumentation of the original interpreter. While it does not give the performance improvements of hand-crafted native compilers, our system provides an appealing point on the language implementation spectrum.

Software code caches are increasingly being used to amortize the runtime overhead of dynamic optimizers, simulators, emulators, dynamic translators, dynamic compilers, and other tools. Despite the now-widespread use of code caches, techniques for efficiently sharing them across multiple threads have not been fully explored. Some systems simply do not support threads, while others resort to thread-private code caches. Although thread-private caches are much simpler to manage, synchronize, and provide scratch space for, they simply do not scale when applied to many-threaded programs. Thread-shared code caches are needed to target server applications, which employ hundreds of worker threads all performing similar tasks. Yet, those systems that do share their code caches often have bruteforce, inefficient solutions to the challenges of concurrent code cache access: a single global lock on runtime system code and suspension of all threads for any cache management action. This limits the possibilities for cache design and has performance problems with applications that require frequent cache invalidations to maintain cache consistency.In this paper, we discuss the design choices when building thread-shared code caches and enumerate the difficulties of thread-local storage, synchronization, trace building, in-cache lookup tables, and cache eviction. We present efficient solutions to these problems that both scale well and do not require thread suspension. We evaluate our results in DynamoRIO, an industrial-strength dynamic binary translation system, on real-world server applications. On these applications our thread-shared caches use an order of magnitude less memory and improve throughput by up to four times compared to threadprivate caches.

Expanded access is a regulatory mechanism by which an investigational drug can be made available outside of a clinical trial to treat patients with serious or life-threatening conditions for which there are no satisfactory treatment options. An expanded access program (EAP) is the formal plan under which preapproval access to an investigational drug can be provided to a group of patients. Although an EAP is a regulated program, the decision to authorize an EAP is the responsibility of the biopharmaceutical sponsor. Because of the significant impact an EAP can have on current patients, drug development, and future patients, we propose that a sponsor’s decision must be based not only on regulatory criteria but also on ethical and practical considerations regarding implementation of an EAP. Such an approach will help ensure that decisions and plans uphold ethical precepts such as fairness, promoting good, and minimizing risk of harm.