We offer a new metric for big data platforms, COST, or the Configuration that Outperforms a Single Thread. The COST of a given platform for a given problem is the hardware configuration required before the platform out-performs a competent single-threaded implementation. COST weighs a system’s scalability against the over-heads introduced by the system, and indicates the actual performance gains of the system, without rewarding sys-tems that bring substantial but parallelizable overheads. We survey measurements of data-parallel systems re-cently reported in SOSP and OSDI, and find that many systems have either a surprisingly large COST, often hundreds of cores, or simply underperform one thread for all of their reported configurations.
While computers with tens of thousands of processors have successfully delivered high performance po...
In the last decades, high-performance large-scale systems have been a fundamental tool for scientifi...
Programming, understanding, and tuning the performance of large multiprocessor systems is challengin...
We offer a new metric for big data platforms, COST, or the Configuration that Outperforms a Single T...
The concept of scalability in parallel systems is a simple one: given a reasonable performance on a ...
Rapid advances in digital sensors, networks, storage, and computation along with their availability ...
. Demand-driven systems follow the model where customers enter the system, request some service, and...
ABSTRACT. High-Performance Computing Systems (HPCS) based on parallel processing have the potential ...
Scalability studies of parallel architectures have used scalar metrics to evaluate their performance...
The For the last three decades, end-to-end computing paradigms, such as MPI (Message Passing Interfa...
High-end supercomputers are increasingly built out of commodity components, and lack tight integrati...
As the amount of simultaneous users of distributed systems increase, scalability is becoming an impo...
peak and achievable performance. One of the conclusions that can be drawn from these benchmarks is t...
High-end supercomputers are increasingly built out of commodity components, and lack tight integrati...
We assess gains from parallel computation on Backlight supercomputer. The information transfers are ...
While computers with tens of thousands of processors have successfully delivered high performance po...
In the last decades, high-performance large-scale systems have been a fundamental tool for scientifi...
Programming, understanding, and tuning the performance of large multiprocessor systems is challengin...
We offer a new metric for big data platforms, COST, or the Configuration that Outperforms a Single T...
The concept of scalability in parallel systems is a simple one: given a reasonable performance on a ...
Rapid advances in digital sensors, networks, storage, and computation along with their availability ...
. Demand-driven systems follow the model where customers enter the system, request some service, and...
ABSTRACT. High-Performance Computing Systems (HPCS) based on parallel processing have the potential ...
Scalability studies of parallel architectures have used scalar metrics to evaluate their performance...
The For the last three decades, end-to-end computing paradigms, such as MPI (Message Passing Interfa...
High-end supercomputers are increasingly built out of commodity components, and lack tight integrati...
As the amount of simultaneous users of distributed systems increase, scalability is becoming an impo...
peak and achievable performance. One of the conclusions that can be drawn from these benchmarks is t...
High-end supercomputers are increasingly built out of commodity components, and lack tight integrati...
We assess gains from parallel computation on Backlight supercomputer. The information transfers are ...
While computers with tens of thousands of processors have successfully delivered high performance po...
In the last decades, high-performance large-scale systems have been a fundamental tool for scientifi...
Programming, understanding, and tuning the performance of large multiprocessor systems is challengin...