Finnish Americans and the Farm Revolt of the 1930s

Farm protest in the United States attracted widespread attention in the 1930s as militant farmers interfered with foreclosure sales, demonstrated at county court houses and state capitals, and blocked highways and stopped trains to prevent crops and livestock from going to market in an effort to raise farm prices. The best known of the protest groups was the Farmers Holiday Association, which was formed in 1932. Prior to the Holiday, however, a left-wing group organized by Communists in 1930 known as the United Farmers League (UFL) gained an initial following in the cutover country of the Upper Peninsula of Michigan, northern Wisconsin, northern Minnesota, and parts of the Dakotas and northeast Montana. Finnish Americans dominated the UFL in the Upper Midwest and in a few locales in the Dakotas. Evidence for this high level of influence comes from the fact that the head of the Communist Party’s Agrarian Department was Henry Puro, a key figure in Finnish American Communist circles and a member of the Party’s Politburo. This paper will focus on Finnish American involvement in the UFL and, to a lesser extent, the broader-based Farmers Holiday movement.

Memory resource balancing for virtualized computing

Virtualization has become a common abstraction layer in modern data centers. By multiplexing hardware resources into multiple virtual machines (VMs) and thus enabling several operating systems to run on the same physical platform simultaneously, it can effectively reduce power consumption and building size or improve security by isolating VMs. In a virtualized system, memory resource management plays a critical role in achieving high resource utilization and performance. Insufficient memory allocation to a VM will degrade its performance dramatically. On the contrary, over-allocation causes waste of memory resources. Meanwhile, a VM’s memory demand may vary significantly. As a result, effective memory resource management calls for a dynamic memory balancer, which, ideally, can adjust memory allocation in a timely manner for each VM based on their current memory demand and thus achieve the best memory utilization and the optimal overall performance. In order to estimate the memory demand of each VM and to arbitrate possible memory resource contention, a widely proposed approach is to construct an LRU-based miss ratio curve (MRC), which provides not only the current working set size (WSS) but also the correlation between performance and the target memory allocation size. Unfortunately, the cost of constructing an MRC is nontrivial. In this dissertation, we first present a low overhead LRU-based memory demand tracking scheme, which includes three orthogonal optimizations: AVL-based LRU organization, dynamic hot set sizing and intermittent memory tracking. Our evaluation results show that, for the whole SPEC CPU 2006 benchmark suite, after applying the three optimizing techniques, the mean overhead of MRC construction is lowered from 173% to only 2%. Based on current WSS, we then predict its trend in the near future and take different strategies for different prediction results. When there is a sufficient amount of physical memory on the host, it locally balances its memory resource for the VMs. Once the local memory resource is insufficient and the memory pressure is predicted to sustain for a sufficiently long time, a relatively expensive solution, VM live migration, is used to move one or more VMs from the hot host to other host(s). Finally, for transient memory pressure, a remote cache is used to alleviate the temporary performance penalty. Our experimental results show that this design achieves 49% center-wide speedup.