Fast DRAM increasingly dominates infrastructure spend in large scale computing environments and this trend will likely worsen without an architectural shift. The cost of deployed memory can be reduced by replacing part of the conventional DRAM with lower cost albeit slower memory media, thus creating a tiered memory system where both tiers are directly addressable and cached. But, this poses numerous challenges in a highly multi-tenant warehouse-scale computing setting. The diversity and scale of its applications motivates an application-transparent solution in the general case, adaptable to specific workload demands.

Real-time Garbage Collection (RTGC) has recently advanced to the point where it is being used in production for financial trading, military command-and-control, and telecommunications. However, among potential users of RTGC, there is enormous diversity in both application requirements and deployment environments.

We describe a general technique for building abstract interpreters over powerful universally quantified abstract domains that leverage existing quantifier-free domains. Our quantified abstract domain can represent universally quantified facts like ∀i(0 ≤ i < n ⇒ α[i] = 0). The principal challenge in this effort is that, while most domains supply over-approximations of operations like join, meet, and variable elimination, working with the guards of quantified facts requires under-approximation. We present an automatic technique to convert the standard over-approximation operations provided with all domains into sound under-approximations. We establish the correctness of our abstract interpreters by identifying two lattices---one that establishes the soundness of the abstract interpreter and another that defines its precision, or completeness. Our experiments on a variety of programs using arrays and pointers (including several sorting algorithms) demonstrate the feasibility of the approach on challenging examples.

The movement to multi-core processors increases the need for simpler, more robust parallel programming models. Atomic sections have been widely recognized for their ease of use. They are simpler and safer to use than manual locking and they increase modularity. But existing proposals have several practical problems, including high overhead and poor interaction with I/O. We present pessimistic atomic sections, a fresh approach that retains many of the advantages of optimistic atomic sections as seen in "transactional memory" without sacrificing performance or compatibility. Pessimistic atomic sections employ the locking mechanisms familiar to programmers while relieving them of most burdens of lock-based programming, including deadlocks. Significantly, pessimistic atomic sections separate correctness from performance: they allow programmers to extract more parallelism via finer-grained locking without fear of introducing bugs. We believe this property is crucial for exploiting multi-core processor designs.We describe a tool, Autolocker, that automatically converts pessimistic atomic sections into standard lock-based code. Autolocker relies extensively on program analysis to determine a correct locking policy free of deadlocks and race conditions. We evaluate the expressiveness of Autolocker by modifying a 50,000 line high-performance web server to use atomic sections while retaining the original locking policy. We analyze Autolocker's performance using microbenchmarks, where Autolocker outperforms software transactional memory by more than a factor of 3.

The C language is among the most widely used in the world, particularly for critical infrastructure software. C programs depend upon macros processed using the C preprocessor, but these macros are difficult to analyze and are often error-prone[4]. Existing tools that analyze and transform C source code have rudimentary support for the preprocessor, leading to obscure error messages and difficulty refactoring. We present a three part solution: (1) a replacement macro language, ASTEC, that addresses the most important important deficiencies of the preprocessor and that eliminates many of the errors it introduces; (2) a translator, MACROSCOPE, that converts existing code into ASTEC semi-automatically; and (3), an ASTEC-aware refactoring tool that handles preprocessor constructs naturally.ASTEC's primary benefits are its analyzability and its refactorability. We present several refactorings that are enabled by ASTEC. Additionally, ASTEC eliminates many of the sources of errors that can plague C preprocessor macros; Ernst et al.[4] estimate that more than 20% of macros may contain errors. In this paper, we describe our translation and refactoring tools and evaluate them on a suite of programs including OpenSSH and the Linux kernel.