Adrián Cristal Kestelman

Mth: Codesigned Hardware/Software Support for Fine Grain Threads

Multi-core processors are ubiquitous in all market segments from embedded to high performance computing, but only few applications can efficiently utilize them. Existing parallel frameworks aim to support thread-level parallelism in applications, but the imposed overhead prevents their usage for small problem instances. This work presents Micro-threads (Mth) a hardware-software proposal focused on a shared thread management model enabling the use of parallel resources in applications that have small chunks of parallel code or small problem inputs by a combination of software and hardware: delegation of the resource control to the application, an improved mechanism to store and fill processors context, and an efficient synchronization system. Four sample applications are used to test our proposal: HSL filter (trivially parallel), FFT Radix2 (recursive algorithm), LU decomposition (barrier every cycle) and Dantzig algorithm (graph based, matrix manipulation). The results encourage the use of Mth and could smooth the use of multiple cores for applications that currently can not take advantage of the proliferation of the available parallel resources in each chip.

Accelerating Hash-Based Query Processing Operations on FPGAs by a Hash Table Caching Technique

Extracting valuable information from the rapidly growing field of Big Data faces serious performance constraints, especially in the software-based database management systems (DBMS). In a query processing system, hash-based computational primitives such as the hash join and the group-by are the most time-consuming operations, as they frequently need to access the hash table on the high-latency off-chip memories and also to traverse whole the table. Subsequently, the hash collision is an inherent issue related to the hash tables, which can adversely degrade the overall performance.