Algorithms that exhibit irregular memory access patterns are known to show poor performance on multiprocessor architectures, particularly when memory access latency is variable. Many common data structures, including graphs, trees, and linked-lists, exhibit these irregular memory access patterns. While FPGA-based code accelerators have been successful on applications with regular memory access patterns, they have not been further explored for irregular memory access patterns. Multithreading has been shown to be an effective technique in masking long latencies. We describe the compiler generation of concurrent hardware threads for FPGAs with the objective of masking the memory latency caused by irregular memory access patterns. The CHAT comp...
The recent emergence of large-scale knowledge discovery, data mining and social network analysis, ir...
Inexpensive DRAMs have created new opportunities for in-memory data analytics. However, the major bo...
Since the era of vector and pipelined computing, the computational speed is limited by the memory ac...
Algorithms that exhibit irregular memory access patterns are known to show poor performance on multi...
The performance gap between CPUs, and memory memory has diverged significantly since the 1980's maki...
The last two decade has witnessed two opposing hardware trends where the DRAM capacity and the acces...
Long memory latencies are mitigated through the use of large cache hierarchies in multi-core archite...
With computing systems becoming ubiquitous, numerous data sets of extremely large size are becoming ...
The Legup High-Level Synthesis (HLS) tool permits the synthesis of multi-threaded software into para...
The increase in size and decrease in cost of DRAMs has led to a rapid growth of in-memory solutions ...
With speculative thread-level parallelization, codes that cannot be fully compiler-analyzed are aggr...
Efficient inter-thread value communication is essential for improving performance in thread-level sp...
Over the past few years there has been increased interest in building custom computing machines (CCM...
Recent trends in hardware have dramatically dropped the price of RAM and shifted focus from systems ...
Multithreading is a well-known technique for general-purpose systems to deliver a substantial perfor...
The recent emergence of large-scale knowledge discovery, data mining and social network analysis, ir...
Inexpensive DRAMs have created new opportunities for in-memory data analytics. However, the major bo...
Since the era of vector and pipelined computing, the computational speed is limited by the memory ac...
Algorithms that exhibit irregular memory access patterns are known to show poor performance on multi...
The performance gap between CPUs, and memory memory has diverged significantly since the 1980's maki...
The last two decade has witnessed two opposing hardware trends where the DRAM capacity and the acces...
Long memory latencies are mitigated through the use of large cache hierarchies in multi-core archite...
With computing systems becoming ubiquitous, numerous data sets of extremely large size are becoming ...
The Legup High-Level Synthesis (HLS) tool permits the synthesis of multi-threaded software into para...
The increase in size and decrease in cost of DRAMs has led to a rapid growth of in-memory solutions ...
With speculative thread-level parallelization, codes that cannot be fully compiler-analyzed are aggr...
Efficient inter-thread value communication is essential for improving performance in thread-level sp...
Over the past few years there has been increased interest in building custom computing machines (CCM...
Recent trends in hardware have dramatically dropped the price of RAM and shifted focus from systems ...
Multithreading is a well-known technique for general-purpose systems to deliver a substantial perfor...
The recent emergence of large-scale knowledge discovery, data mining and social network analysis, ir...
Inexpensive DRAMs have created new opportunities for in-memory data analytics. However, the major bo...
Since the era of vector and pipelined computing, the computational speed is limited by the memory ac...