Communications - November 2010

ceed independently of all the others. Any synchronization required within these subtasks can be localized to the subtasks. Only at the end, when all subsequent operations are merged, must the parallel subtasks be synchronized with one another. Organizing synchronization hierarchically also aligns well with the physical cost of synchronizing threads spread across different sections of a given system. It is natural to expect that threads executing on a single core can be synchronized much more cheaply than threads spread across an entire processor, just as threads on a single machine can be synchronized more cheaply than threads across the multiple nodes of a cluster.

conclusion

The transition from single-core to multicore processors and the increasing use of throughout-oriented architectures signal greater emphasis on parallelism as the driving force for higher computational performance. Yet these two kinds of processors differ in the degree of parallelism they expect to encounter in a typical workload. Throughput-oriented processors assume parallelism is abundant, rather than scarce, and their paramount design goal is maximizing total throughput of all parallel tasks rather than minimizing the latency of a single sequential task.

Emphasizing total throughput over the running time of a single task leads to a number of architectural design decisions. Among them, the three primary architectural trends typical of throughput-oriented processors are hardware multithreading, many simple processing elements, and SIMD execution. Hardware multithreading makes managing the expected abundant parallelism cheap. Simple in-order cores forgo out-of-order execution and speculation, and SIMD execution increases the ratio of functional units to control logic. Simple core design and SIMD execution reduce the area and power cost of control logic, leaving more resources for parallel functional units.

These design decisions are all predi-
cated on the assumption that sufficient
parallelism exists in the workloads the
processor is expected to handle. The
performance of a program with insuf-
ficient parallelism may therefore suffer.
A fully general-purpose chip (such as a
CPU) cannot afford to aggressively trade
for increased total performance at the
cost of single-thread performance. The
spectrum of workloads presented to it
is simply too broad, and not all compu-
tations are parallel. For computations
that are largely sequential, latency-ori-
ented processors perform better than
throughput-oriented processors. On
the other hand, a processor specifically
intended for parallel computation can
accept this trade-off and realize signifi-
cantly greater total throughput on paral-
lel problems as a result.

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