James R. Larus

TL;DR: The authors deployed the reconfigurable fabric in a bed of 1,632 servers and FPGAs in a production datacenter and successfully used it to accelerate the ranking portion of the Bing Web search engine by nearly a factor of two.

TL;DR: In this article, a machine learning approach is proposed to discover formal specifications of the protocols that code must obey when interacting with an application program interface or abstract data type, starting from the assumption that a working program is well enough debugged to reveal strong hints of correct protocols, and concisely summarizing the frequent interaction patterns as state machines that capture both temporal and data dependences.

TL;DR: The requirements and architecture of the fabric are described, the critical engineering challenges and solutions needed to make the system robust in the presence of failures are detailed, and the performance, power, and resilience of the system when ranking candidate documents are measured.

TL;DR: A new algorithm for path profiling is described, which selects and places profile instrumentation to minimize run-time overhead and identifies longer paths than a previous technique, which predicted paths from edge profiles.

TL;DR: The introductory article in this issue describes the hardware imperatives behind this shift in computer architecture from uniprocessors to multicore processors, also known as CMPs.